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Sample records for automated clinical decision

  1. Automated Modular Magnetic Resonance Imaging Clinical Decision Support System (MIROR): An Application in Pediatric Cancer Diagnosis.

    Science.gov (United States)

    Zarinabad, Niloufar; Meeus, Emma M; Manias, Karen; Foster, Katharine; Peet, Andrew

    2018-05-02

    Advances in magnetic resonance imaging and the introduction of clinical decision support systems has underlined the need for an analysis tool to extract and analyze relevant information from magnetic resonance imaging data to aid decision making, prevent errors, and enhance health care. The aim of this study was to design and develop a modular medical image region of interest analysis tool and repository (MIROR) for automatic processing, classification, evaluation, and representation of advanced magnetic resonance imaging data. The clinical decision support system was developed and evaluated for diffusion-weighted imaging of body tumors in children (cohort of 48 children, with 37 malignant and 11 benign tumors). Mevislab software and Python have been used for the development of MIROR. Regions of interests were drawn around benign and malignant body tumors on different diffusion parametric maps, and extracted information was used to discriminate the malignant tumors from benign tumors. Using MIROR, the various histogram parameters derived for each tumor case when compared with the information in the repository provided additional information for tumor characterization and facilitated the discrimination between benign and malignant tumors. Clinical decision support system cross-validation showed high sensitivity and specificity in discriminating between these tumor groups using histogram parameters. MIROR, as a diagnostic tool and repository, allowed the interpretation and analysis of magnetic resonance imaging images to be more accessible and comprehensive for clinicians. It aims to increase clinicians' skillset by introducing newer techniques and up-to-date findings to their repertoire and make information from previous cases available to aid decision making. The modular-based format of the tool allows integration of analyses that are not readily available clinically and streamlines the future developments. ©Niloufar Zarinabad, Emma M Meeus, Karen Manias

  2. Automation in Clinical Microbiology

    Science.gov (United States)

    Ledeboer, Nathan A.

    2013-01-01

    Historically, the trend toward automation in clinical pathology laboratories has largely bypassed the clinical microbiology laboratory. In this article, we review the historical impediments to automation in the microbiology laboratory and offer insight into the reasons why we believe that we are on the cusp of a dramatic change that will sweep a wave of automation into clinical microbiology laboratories. We review the currently available specimen-processing instruments as well as the total laboratory automation solutions. Lastly, we outline the types of studies that will need to be performed to fully assess the benefits of automation in microbiology laboratories. PMID:23515547

  3. Selecting automation for the clinical chemistry laboratory.

    Science.gov (United States)

    Melanson, Stacy E F; Lindeman, Neal I; Jarolim, Petr

    2007-07-01

    Laboratory automation proposes to improve the quality and efficiency of laboratory operations, and may provide a solution to the quality demands and staff shortages faced by today's clinical laboratories. Several vendors offer automation systems in the United States, with both subtle and obvious differences. Arriving at a decision to automate, and the ensuing evaluation of available products, can be time-consuming and challenging. Although considerable discussion concerning the decision to automate has been published, relatively little attention has been paid to the process of evaluating and selecting automation systems. To outline a process for evaluating and selecting automation systems as a reference for laboratories contemplating laboratory automation. Our Clinical Chemistry Laboratory staff recently evaluated all major laboratory automation systems in the United States, with their respective chemistry and immunochemistry analyzers. Our experience is described and organized according to the selection process, the important considerations in clinical chemistry automation, decisions and implementation, and we give conclusions pertaining to this experience. Including the formation of a committee, workflow analysis, submitting a request for proposal, site visits, and making a final decision, the process of selecting chemistry automation took approximately 14 months. We outline important considerations in automation design, preanalytical processing, analyzer selection, postanalytical storage, and data management. Selecting clinical chemistry laboratory automation is a complex, time-consuming process. Laboratories considering laboratory automation may benefit from the concise overview and narrative and tabular suggestions provided.

  4. Designing an automated clinical decision support system to match clinical practice guidelines for opioid therapy for chronic pain

    Directory of Open Access Journals (Sweden)

    Clark Michael E

    2010-04-01

    Full Text Available Abstract Background Opioid prescribing for chronic pain is common and controversial, but recommended clinical practices are followed inconsistently in many clinical settings. Strategies for increasing adherence to clinical practice guideline recommendations are needed to increase effectiveness and reduce negative consequences of opioid prescribing in chronic pain patients. Methods Here we describe the process and outcomes of a project to operationalize the 2003 VA/DOD Clinical Practice Guideline for Opioid Therapy for Chronic Non-Cancer Pain into a computerized decision support system (DSS to encourage good opioid prescribing practices during primary care visits. We based the DSS on the existing ATHENA-DSS. We used an iterative process of design, testing, and revision of the DSS by a diverse team including guideline authors, medical informatics experts, clinical content experts, and end-users to convert the written clinical practice guideline into a computable algorithm to generate patient-specific recommendations for care based upon existing information in the electronic medical record (EMR, and a set of clinical tools. Results The iterative revision process identified numerous and varied problems with the initially designed system despite diverse expert participation in the design process. The process of operationalizing the guideline identified areas in which the guideline was vague, left decisions to clinical judgment, or required clarification of detail to insure safe clinical implementation. The revisions led to workable solutions to problems, defined the limits of the DSS and its utility in clinical practice, improved integration into clinical workflow, and improved the clarity and accuracy of system recommendations and tools. Conclusions Use of this iterative process led to development of a multifunctional DSS that met the approval of the clinical practice guideline authors, content experts, and clinicians involved in testing. The

  5. Datafication of Automated (Legal) Decisions

    DEFF Research Database (Denmark)

    Schaumburg-Müller, Sten

    Even though I maintain that it is a misconception to state that states are “no longer” the only actors, since they never were, indeed it makes sense to “shed light on the impact of (…) new tendencies on legal regulatory mechanisms (…)” One regulatory tendency is obviously the automation of (legal......) decisions which has implications for legal orders, legal actors and legal research, not to mention legal legitimacy as well as personal autonomy and democracy. On the one hand automation may facilitate better, faster, more predictable and more coherent decisions and leave cumbersome and time consuming...... a substantial part of the components of the decisions are prefabricated. With a risk of misplacing the responsibility, this may be called the “google syndrome”. The hidden algorithms may also constitute the basis for decisions concerning individuals (the passive aspect), the “profiling syndrome”. Based on big...

  6. Implementation of a scalable, web-based, automated clinical decision support risk-prediction tool for chronic kidney disease using C-CDA and application programming interfaces.

    Science.gov (United States)

    Samal, Lipika; D'Amore, John D; Bates, David W; Wright, Adam

    2017-11-01

    Clinical decision support tools for risk prediction are readily available, but typically require workflow interruptions and manual data entry so are rarely used. Due to new data interoperability standards for electronic health records (EHRs), other options are available. As a clinical case study, we sought to build a scalable, web-based system that would automate calculation of kidney failure risk and display clinical decision support to users in primary care practices. We developed a single-page application, web server, database, and application programming interface to calculate and display kidney failure risk. Data were extracted from the EHR using the Consolidated Clinical Document Architecture interoperability standard for Continuity of Care Documents (CCDs). EHR users were presented with a noninterruptive alert on the patient's summary screen and a hyperlink to details and recommendations provided through a web application. Clinic schedules and CCDs were retrieved using existing application programming interfaces to the EHR, and we provided a clinical decision support hyperlink to the EHR as a service. We debugged a series of terminology and technical issues. The application was validated with data from 255 patients and subsequently deployed to 10 primary care clinics where, over the course of 1 year, 569 533 CCD documents were processed. We validated the use of interoperable documents and open-source components to develop a low-cost tool for automated clinical decision support. Since Consolidated Clinical Document Architecture-based data extraction extends to any certified EHR, this demonstrates a successful modular approach to clinical decision support. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  7. An Automated System for Generating Situation-Specific Decision Support in Clinical Order Entry from Local Empirical Data

    Science.gov (United States)

    Klann, Jeffrey G.

    2011-01-01

    Clinical Decision Support is one of the only aspects of health information technology that has demonstrated decreased costs and increased quality in healthcare delivery, yet it is extremely expensive and time-consuming to create, maintain, and localize. Consequently, a majority of health care systems do not utilize it, and even when it is…

  8. A Review of Automated Decision Support System

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... Intelligence AI that enable decision automation based on existing facts, knowledge ... The growing reliance on data impacts dynamic data extraction and retrieval of the ... entertainment, medical, and the web. III. DECISION ...

  9. Automated Decision Tree Classification of Corneal Shape

    Science.gov (United States)

    Twa, Michael D.; Parthasarathy, Srinivasan; Roberts, Cynthia; Mahmoud, Ashraf M.; Raasch, Thomas W.; Bullimore, Mark A.

    2011-01-01

    Purpose The volume and complexity of data produced during videokeratography examinations present a challenge of interpretation. As a consequence, results are often analyzed qualitatively by subjective pattern recognition or reduced to comparisons of summary indices. We describe the application of decision tree induction, an automated machine learning classification method, to discriminate between normal and keratoconic corneal shapes in an objective and quantitative way. We then compared this method with other known classification methods. Methods The corneal surface was modeled with a seventh-order Zernike polynomial for 132 normal eyes of 92 subjects and 112 eyes of 71 subjects diagnosed with keratoconus. A decision tree classifier was induced using the C4.5 algorithm, and its classification performance was compared with the modified Rabinowitz–McDonnell index, Schwiegerling’s Z3 index (Z3), Keratoconus Prediction Index (KPI), KISA%, and Cone Location and Magnitude Index using recommended classification thresholds for each method. We also evaluated the area under the receiver operator characteristic (ROC) curve for each classification method. Results Our decision tree classifier performed equal to or better than the other classifiers tested: accuracy was 92% and the area under the ROC curve was 0.97. Our decision tree classifier reduced the information needed to distinguish between normal and keratoconus eyes using four of 36 Zernike polynomial coefficients. The four surface features selected as classification attributes by the decision tree method were inferior elevation, greater sagittal depth, oblique toricity, and trefoil. Conclusions Automated decision tree classification of corneal shape through Zernike polynomials is an accurate quantitative method of classification that is interpretable and can be generated from any instrument platform capable of raw elevation data output. This method of pattern classification is extendable to other classification

  10. Automating Performance Measures and Clinical Practice Guidelines: Differences and Complementarities.

    Science.gov (United States)

    Tu, Samson W; Martins, Susana; Oshiro, Connie; Yuen, Kaeli; Wang, Dan; Robinson, Amy; Ashcraft, Michael; Heidenreich, Paul A; Goldstein, Mary K

    2016-01-01

    Through close analysis of two pairs of systems that implement the automated evaluation of performance measures (PMs) and guideline-based clinical decision support (CDS), we contrast differences in their knowledge encoding and necessary changes to a CDS system that provides management recommendations for patients failing performance measures. We trace the sources of differences to the implementation environments and goals of PMs and CDS.

  11. Automated Sleep Stage Scoring by Decision Tree Learning

    National Research Council Canada - National Science Library

    Hanaoka, Masaaki

    2001-01-01

    In this paper we describe a waveform recognition method that extracts characteristic parameters from wave- forms and a method of automated sleep stage scoring using decision tree learning that is in...

  12. An automated approach to the design of decision tree classifiers

    Science.gov (United States)

    Argentiero, P.; Chin, R.; Beaudet, P.

    1982-01-01

    An automated technique is presented for designing effective decision tree classifiers predicated only on a priori class statistics. The procedure relies on linear feature extractions and Bayes table look-up decision rules. Associated error matrices are computed and utilized to provide an optimal design of the decision tree at each so-called 'node'. A by-product of this procedure is a simple algorithm for computing the global probability of correct classification assuming the statistical independence of the decision rules. Attention is given to a more precise definition of decision tree classification, the mathematical details on the technique for automated decision tree design, and an example of a simple application of the procedure using class statistics acquired from an actual Landsat scene.

  13. Automation in the clinical microbiology laboratory.

    Science.gov (United States)

    Novak, Susan M; Marlowe, Elizabeth M

    2013-09-01

    Imagine a clinical microbiology laboratory where a patient's specimens are placed on a conveyor belt and sent on an automation line for processing and plating. Technologists need only log onto a computer to visualize the images of a culture and send to a mass spectrometer for identification. Once a pathogen is identified, the system knows to send the colony for susceptibility testing. This is the future of the clinical microbiology laboratory. This article outlines the operational and staffing challenges facing clinical microbiology laboratories and the evolution of automation that is shaping the way laboratory medicine will be practiced in the future. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Clinical Decision Support (CDS) Inventory

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Clinical Decision Support (CDS) Inventory contains descriptions of past and present CDS projects across the Federal Government. It includes Federal projects,...

  15. The Level of Automation in Emergency Quick Disconnect Decision Making

    Directory of Open Access Journals (Sweden)

    Imset Marius

    2018-02-01

    Full Text Available As a key measure for safety and environmental protection during offshore well operations, drill rigs are equipped with Emergency Quick Disconnect (EQD systems. However, an EQD operation is in itself considered a risky operation with a major economic impact. For this reason, it is of great importance to aid the operators in their assessment of the situation at all times, and help them make the best decisions. However, despite the availability of such systems, accidents do happen. This demonstrates the vulnerability of our human decision-making capabilities in extremely stressful situations. One way of improving the overall human-system performance with respect to EQD is to increase the level and quality of the automation and decision support systems. Although there is plenty of evidence that automated systems have weaknesses, there is also evidence that advanced software systems outperform humans in complex decision-making. The major challenge is to make sure that EQD is performed when necessary, but there is also a need to decrease the number of false EQDs. This paper applies an existing framework for levels of automation in order to explore the critical decision process leading to an EQD. We provide an overview of the benefits and drawbacks of existing automation and decision support systems vs. manual human decision-making. Data are collected from interviews of offshore users, suppliers, and oil companies, as well as from formal operational procedures. Findings are discussed using an established framework for the level of automation. Our conclusion is that there is an appropriate level of automation in critical situations related to the loss of the position of the drill rig, and that there is the promising potential to increase the autonomy level in a mid- and long-term situation assessment.

  16. Automated Vectorization of Decision-Based Algorithms

    Science.gov (United States)

    James, Mark

    2006-01-01

    Virtually all existing vectorization algorithms are designed to only analyze the numeric properties of an algorithm and distribute those elements across multiple processors. This advances the state of the practice because it is the only known system, at the time of this reporting, that takes high-level statements and analyzes them for their decision properties and converts them to a form that allows them to automatically be executed in parallel. The software takes a high-level source program that describes a complex decision- based condition and rewrites it as a disjunctive set of component Boolean relations that can then be executed in parallel. This is important because parallel architectures are becoming more commonplace in conventional systems and they have always been present in NASA flight systems. This technology allows one to take existing condition-based code and automatically vectorize it so it naturally decomposes across parallel architectures.

  17. Automated radiochemical processing for clinical PET

    International Nuclear Information System (INIS)

    Padgett, H.C.; Schmidt, D.G.; Bida, G.T.; Wieland, B.W.; Pekrul, E.; Kingsbury, W.G.

    1991-01-01

    With the recent emergence of positron emission tomography (PET) as a viable clinical tool, there is a need for a convenient, cost-effective source of the positron emitter-labeled radiotracers labeled with carbon-11, nitrogen-13, oxygen-15, and fluorine-18. These short-lived radioisotopes are accelerator produced and thus, require a cyclotron and radiochemistry processing instrumentation that can be operated 3 in a clinical environment by competant technicians. The basic goal is to ensure safety and reliability while setting new standards for economy and ease of operation. The Siemens Radioisotope Delivery System (RDS 112) is a fully automated system dedicated to the production and delivery of positron-emitter labeled precursors and radiochemicals required to support a clinical PET imaging program. Thus, the entire RDS can be thought of as an automated radiochemical processing apparatus

  18. [Cognitive traps and clinical decisions].

    Science.gov (United States)

    Motterlini, Matteo

    2017-12-01

    We are fallible, we have limited computational capabilities, limited access to information, little memory. Moreover, in everyday life, we feel joy, fear, anger, and other emotions that influence our decisions in a little, "calculated" way. Not everyone, however, is also aware that the mistakes we make are often systematic and therefore, in particular circumstances, are foreseeable. Doctors and patients are constantly called upon to make decisions. They need to identify relevant information (for example, the symptoms or outcome of an examination), formulate a judgment (for example a diagnosis), choose an action course among the various possible ones based on one's own preferences (e.g. medication or surgery), so act. The exact size of the medical error is unknown, but probably huge. In fact, the more we investigate and the more we find. Often these mistakes depend on the cognitive process. Any (rational) decision requires, in particular, an assessment of the possible effects of the action it implements; for example how much pleasure or pain it will cause us. In the medical field, too, the principle of informed consent provides that the patient's preferences and values are to guide clinical choices. Yet, not always the preferences that people express before making an experience match with their preferences after living that experience. Some ingenious experiments suggest (in a seemingly paradoxical way) that before a direct experience, people prefer less pain; after that experience they prefer more, but with a better memory.

  19. A Decision Support Framework for Automated Screening of Diabetic Retinopathy

    Directory of Open Access Journals (Sweden)

    2006-01-01

    Full Text Available The early signs of diabetic retinopathy (DR are depicted by microaneurysms among other signs. A prompt diagnosis when the disease is at the early stage can help prevent irreversible damages to the diabetic eye. In this paper, we propose a decision support system (DSS for automated screening of early signs of diabetic retinopathy. Classification schemes for deducing the presence or absence of DR are developed and tested. The detection rule is based on binary-hypothesis testing problem which simplifies the problem to yes/no decisions. An analysis of the performance of the Bayes optimality criteria applied to DR is also presented. The proposed DSS is evaluated on the real-world data. The results suggest that by biasing the classifier towards DR detection, it is possible to make the classifier achieve good sensitivity.

  20. Automated Whole Brain Tractography Affects Preoperative Surgical Decision Making.

    Science.gov (United States)

    Zakaria, Hesham; Haider, Sameah; Lee, Ian

    2017-09-06

    Surgery in and around eloquent brain structures poses a technical challenge when the goal of surgery is maximal safe resection. Magnetic resonance imaging (MRI) has revolutionized the diagnosis and treatment of neurological disorders, but tractography still remains limited in terms of utility because of the requisite manual labor and time required combined with the high risk of bias and inaccuracy. Automated whole brain tractography (AWBT) has simplified this workflow, overcoming historical barriers, and allowing for integration into modern neuronavigation. However, current literature showing the usefulness of this new technology is limited. In this study, we aimed to illustrate the utility of AWBT during cranial surgery and its ability to affect presurgical and intraoperative clinical decision making. We performed a retrospective chart review of cases that underwent AWBT for one year from July 2016 to July 2017. All patients underwent conventional anatomic MRI with and without contrast sequences, in addition to diffusion tensor imaging (DTI) on a 3 Tesla MRI scanner (Ingenia 3.0T, Philips, Amsterdam NL). Post-hoc AWBT processing was performed on a separate workstation. Patients were subsequently grouped into those that had undergone either language or motor mapping and those that did not. We compared both sets of patients to see any differences in patient age, sex, laterality of surgery, depth of resection from cortical surface, and smallest distance between the lesion and adjacent eloquent white matter tracts. We identified illustrative cases which demonstrated the ability of AWBT to affect surgical decision making. In this single-center series, we identified 73 total patients who underwent AWBT for intracranial surgery, of which 28 patients underwent either speech or language mapping. When comparing mapping to non-mapping patients, we found no difference with respect to age, gender, laterality of surgery, or whether the surgery was a revision. The distance

  1. Laboratory automation in clinical bacteriology: what system to choose?

    Science.gov (United States)

    Croxatto, A; Prod'hom, G; Faverjon, F; Rochais, Y; Greub, G

    2016-03-01

    Automation was introduced many years ago in several diagnostic disciplines such as chemistry, haematology and molecular biology. The first laboratory automation system for clinical bacteriology was released in 2006, and it rapidly proved its value by increasing productivity, allowing a continuous increase in sample volumes despite limited budgets and personnel shortages. Today, two major manufacturers, BD Kiestra and Copan, are commercializing partial or complete laboratory automation systems for bacteriology. The laboratory automation systems are rapidly evolving to provide improved hardware and software solutions to optimize laboratory efficiency. However, the complex parameters of the laboratory and automation systems must be considered to determine the best system for each given laboratory. We address several topics on laboratory automation that may help clinical bacteriologists to understand the particularities and operative modalities of the different systems. We present (a) a comparison of the engineering and technical features of the various elements composing the two different automated systems currently available, (b) the system workflows of partial and complete laboratory automation, which define the basis for laboratory reorganization required to optimize system efficiency, (c) the concept of digital imaging and telebacteriology, (d) the connectivity of laboratory automation to the laboratory information system, (e) the general advantages and disadvantages as well as the expected impacts provided by laboratory automation and (f) the laboratory data required to conduct a workflow assessment to determine the best configuration of an automated system for the laboratory activities and specificities. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  2. Adjudication Decision Support (ADS) System Automated Approval Estimates for NACLC Investigations

    National Research Council Canada - National Science Library

    Lang, Eric L; Youpa, Daniel G; Berman, Sandi; Leggitt, John S

    2007-01-01

    The present research is the second in a series of studies to test preliminary decision rules and provide automated approval estimates for a Department of Defense Adjudication Decision Support (ADS) system...

  3. Decision Making In A High-Tech World: Automation Bias and Countermeasures

    Science.gov (United States)

    Mosier, Kathleen L.; Skitka, Linda J.; Burdick, Mark R.; Heers, Susan T.; Rosekind, Mark R. (Technical Monitor)

    1996-01-01

    Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and

  4. Patients' Values in Clinical Decision-Making.

    Science.gov (United States)

    Faggion, Clovis Mariano; Pachur, Thorsten; Giannakopoulos, Nikolaos Nikitas

    2017-09-01

    Shared decision-making involves the participation of patient and dental practitioner. Well-informed decision-making requires that both parties understand important concepts that may influence the decision. This fourth article in a series of 4 aims to discuss the importance of patients' values when a clinical decision is made. We report on how to incorporate important concepts for well-informed, shared decision-making. Here, we present patient values as an important issue, in addition to previously established topics such as the risk of bias of a study, cost-effectiveness of treatment approaches, and a comparison of therapeutic benefit with potential side effects. We provide 2 clinical examples and suggestions for a decision tree, based on the available evidence. The information reported in this article may improve the relationship between patient and dental practitioner, resulting in more well-informed clinical decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Adaptive Automation Based on Air Traffic Controller Decision-Making

    NARCIS (Netherlands)

    IJtsma (Student TU Delft), Martijn; Borst, C.; Mercado Velasco, G.A.; Mulder, M.; van Paassen, M.M.; Tsang, P.S.; Vidulich, M.A.

    2017-01-01

    Through smart scheduling and triggering of automation support, adaptive automation has the potential to balance air traffic controller workload. The challenge in the design of adaptive automation systems is to decide how and when the automation should provide support. This paper describes the design

  6. Legal Considerations in Clinical Decision Making.

    Science.gov (United States)

    Ursu, Samuel C.

    1992-01-01

    Discussion of legal issues in dental clinical decision making looks at the nature and elements of applicable law, especially malpractice, locus of responsibility, and standards of care. Greater use of formal decision analysis in clinical dentistry and better research on diagnosis and treatment are recommended, particularly in light of increasing…

  7. How do principles for human-centred automation apply to Disruption Management Decision Support?

    OpenAIRE

    Golightly, David; Dadashi, Nastaran

    2016-01-01

    While automation of signal and route setting is routine, the use of automation or decision support in disruption management processes is far less common. Such support offers significant advantages in optimising re-planning of both timetable and resources (crew and rolling stock), and has value in offering a 'shared view' of re-planning across the many actors manage disruption. If this vision is to be realised, however, disruption management decision support and automation must adhere to prove...

  8. Personalized Clinical Decision Making in Gastrointestinal Malignancies

    DEFF Research Database (Denmark)

    Hess, Søren; Bjerring, Ole Steen; Pfeiffer, Per

    2016-01-01

    and initial stages. This article outlines the potential use of fluorodeoxyglucose-PET/CT in clinical decision making with special regard to preoperative evaluation and response assessment in gastric cancer (including the gastroesophageal junction), pancreatic cancer (excluding neuroendocrine tumors...

  9. Decision analysis. Clinical art or Clinical Science

    Science.gov (United States)

    1977-05-01

    having helped some clients. Over the past half century, psychotherapy has faced a series of crises concerned with its transformation from an art to a...clinical science . These include validation of the effectiveness of various forms of therapy, validating elements of treatment programs and

  10. A conceptual framework for automating the operational and strategic decision-making process in the health care delivery system.

    Science.gov (United States)

    Ruohonen, Toni; Ennejmy, Mohammed

    2013-01-01

    Making reliable and justified operational and strategic decisions is a really challenging task in the health care domain. So far, the decisions have been made based on the experience of managers and staff, or they are evaluated with traditional methods, using inadequate data. As a result of this kind of decision-making process, attempts to improve operations usually have failed or led to only local improvements. Health care organizations have a lot of operational data, in addition to clinical data, which is the key element for making reliable and justified decisions. However, it is progressively problematic to access it and make usage of it. In this paper we discuss about the possibilities how to exploit operational data in the most efficient way in the decision-making process. We'll share our future visions and propose a conceptual framework for automating the decision-making process.

  11. Automation and decision support in interactive consumer products.

    OpenAIRE

    Sauer, J.; Rüttinger, B.

    2007-01-01

    This article presents two empirical studies (n=30, n=48) that are concerned with different forms of automation in interactive consumer products. The goal of the studies was to evaluate the effectiveness of two types of automation: perceptual augmentation (i.e. supporting users' action selection and implementation). Furthermore, the effectiveness of non-product information (i.e. labels attached to product) in supporting automation design was evaluated. The findings suggested greater benefits f...

  12. Clinical evaluation of an automated turning bed.

    Science.gov (United States)

    Melland, H I; Langemo, D; Hanson, D; Olson, B; Hunter, S

    1999-01-01

    The purposes of this study were to assess client comfort and sleep quality, client physiologic response (skin and respiratory status), the effect on the need for caregiver assistance, and cost when using an automated turning bed. Nonexperimental, evaluative study. Twenty-four adult home or long-term care resident subjects who had a degenerative disease, spinal cord injury, stroke, cerebral palsy, or back surgery. Each subject agreed to use the automated turning bed for four weeks. Researchers completed a demographic survey and skin assessment, and assessed each subject for pressure ulcer risk and for the need of assistance of a care giver for turning before and after the four weeks of using the turning bed. Subjects rated the turning bed in terms of comfort and sleep quality. Subjects rated the turning bed as more comfortable than their own bed and expressed satisfaction at the pain relief attained when on the turning bed. While using the turning bed, there was a significant improvement in sleep quality. No skin breakdown or deterioration in respiratory status occurred. Fewer subjects required the assistance of a caregiver for turning when on the turning bed. This automated turning bed shows great promise in meeting a need for patients with limited mobility whether they are homebound or in a residential community. Future studies that further investigate use of the turning bed for postoperative back patients while still in the acute care setting are indicated. Replicative studies with a larger sample size are also indicated.

  13. Studies and Analyses of Aided Adversarial Decision Making. Phase 2: Research on Human Trust in Automation

    National Research Council Canada - National Science Library

    Llinas, James

    1998-01-01

    .... Given that offensive IW operations may interfere with automated, data-fusion based decision aids, it is necessary to understand how personnel may rely on or trust these aids when appropriate (e.g...

  14. Decision Analysis: Engineering Science or Clinical Art

    Science.gov (United States)

    1979-11-01

    TECHNICAL REPORT TR 79-2-97 DECISION ANALYSIS: ENGINEERING SCIENCE OR CLINICAL ART ? by Dennis M. Buede Prepared for Defense Advanced Research...APPLICATIONS OF THE ENGINEER- ING SCIENCE AND CLINICAL ART EXTREMES 9 3.1 Applications of the Engineering Science Approach 9 3.1.1 Mexican electrical...DISCUSSION 29 4.1 Engineering Science versus Clinical Art : A Characterization of When Each is Most Attractive 30 4.2 The Implications of the Engineering

  15. Clinical decision making in veterinary practice

    OpenAIRE

    Everitt, Sally

    2011-01-01

    Aim The aim of this study is to develop an understanding of the factors which influence veterinary surgeons’ clinical decision making during routine consultations. Methods The research takes a qualitative approach using video-cued interviews, in which one of the veterinary surgeon’s own consultations is used as the basis of a semi-structured interview exploring decision making in real cases. The research focuses primarily on small animal consultations in first opinion practice, how...

  16. Assay-specific decision limits for two new automated parathyroid hormone and 25-hydroxyvitamin D assays.

    Science.gov (United States)

    Souberbielle, Jean-Claude; Fayol, Véronique; Sault, Corinne; Lawson-Body, Ethel; Kahan, André; Cormier, Catherine

    2005-02-01

    The recent development of nonradioactive automated assays for serum parathyroid hormone (PTH) and 25-hydroxyvitamin D (25OHD) has made measurement of these two hormones possible in many laboratories. In this study, we compared two new assays for PTH and 25OHD adapted on an automated analyzer, the LIAISON, with two manual immunoassays used worldwide. We studied 228 osteoporotic patients, 927 healthy individuals, 38 patients with primary hyperparathyroidism, and 167 hemodialyzed patients. Serum PTH was measured with the Allegro and the LIAISON assays, and 25OHD was measured with DiaSorin RIA and the LIAISON assay. Regression analysis was used to calculate decision thresholds for the LIAISON assays that were equivalent to those of the Allegro PTH and DiaSorin 25OHD assays. The 25OHD concentrations obtained with the LIAISON assay and the RIA in osteoporotic patients were well correlated (r = 0.83; P 50 nmol/L as eligible for the reference population for the LIAISON PTH assay. In this group, the 3rd-97th percentile interval for LIAISON PTH was 3-51 ng/L. Considering upper reference limits of 46 and 51 ng/L for the Allegro and LIAISON assays, respectively, the frequency of above-normal PTH concentrations in patients with primary hyperparathyroidism was similar in both assays. Regression analysis between serum PTH measured by the Allegro and LIAISON assays in 167 hemodialyzed patients and the corresponding Bland-Altman analysis of these data suggest that the LIAISON PTH assay tends to read higher than the Allegro assay at low concentrations but lower at high concentrations (>300 ng/L). Because clinical decision limits for both PTH and 25OHD should be assay specific, we propose equivalences between these assays and two manual assays used worldwide. These assay-specific decision limits should help potential users of the LIAISON PTH and 25OHD assays.

  17. Clinical decision making: how surgeons do it.

    Science.gov (United States)

    Crebbin, Wendy; Beasley, Spencer W; Watters, David A K

    2013-06-01

    Clinical decision making is a core competency of surgical practice. It involves two distinct types of mental process best considered as the ends of a continuum, ranging from intuitive and subconscious to analytical and conscious. In practice, individual decisions are usually reached by a combination of each, according to the complexity of the situation and the experience/expertise of the surgeon. An expert moves effortlessly along this continuum, according to need, able to apply learned rules or algorithms to specific presentations, choosing these as a result of either pattern recognition or analytical thinking. The expert recognizes and responds quickly to any mismatch between what is observed and what was expected, coping with gaps in information and making decisions even where critical data may be uncertain or unknown. Even for experts, the cognitive processes involved are difficult to articulate as they tend to be very complex. However, if surgeons are to assist trainees in developing their decision-making skills, the processes need to be identified and defined, and the competency needs to be measurable. This paper examines the processes of clinical decision making in three contexts: making a decision about how to manage a patient; preparing for an operative procedure; and reviewing progress during an operative procedure. The models represented here are an exploration of the complexity of the processes, designed to assist surgeons understand how expert clinical decision making occurs and to highlight the challenge of teaching these skills to surgical trainees. © 2013 The Authors. ANZ Journal of Surgery © 2013 Royal Australasian College of Surgeons.

  18. Modelling and Decision Support of Clinical Pathways

    Science.gov (United States)

    Gabriel, Roland; Lux, Thomas

    The German health care market is under a rapid rate of change, forcing especially hospitals to provide high-quality services at low costs. Appropriate measures for more effective and efficient service provision are process orientation and decision support by information technology of clinical pathway of a patient. The essential requirements are adequate modelling of clinical pathways as well as usage of adequate systems, which are capable of assisting the complete path of a patient within a hospital, and preferably also outside of it, in a digital way. To fulfil these specifications the authors present a suitable concept, which meets the challenges of well-structured clinical pathways as well as rather poorly structured diagnostic and therapeutic decisions, by interplay of process-oriented and knowledge-based hospital information systems.

  19. Computerized Clinical Decision Support: Contributions from 2015

    Science.gov (United States)

    Bouaud, J.

    2016-01-01

    Summary Objective To summarize recent research and select the best papers published in 2015 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook. Method A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry (CPOE) systems. The aim was to identify a list of candidate best papers from the retrieved papers that were then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the IMIA editorial team was finally conducted to conclude in the best paper selection. Results Among the 974 retrieved papers, the entire review process resulted in the selection of four best papers. One paper reports on a CDSS routinely applied in pediatrics for more than 10 years, relying on adaptations of the Arden Syntax. Another paper assessed the acceptability and feasibility of an important CPOE evaluation tool in hospitals outside the US where it was developed. The third paper is a systematic, qualitative review, concerning usability flaws of medication-related alerting functions, providing an important evidence-based, methodological contribution in the domain of CDSS design and development in general. Lastly, the fourth paper describes a study quantifying the effect of a complex, continuous-care, guideline-based CDSS on the correctness and completeness of clinicians’ decisions. Conclusions While there are notable examples of routinely used decision support systems, this 2015 review on CDSSs and CPOE systems still shows that, despite methodological contributions, theoretical frameworks, and prototype developments, these technologies are not yet widely spread (at least with their full functionalities) in routine clinical practice. Further research, testing, evaluation, and training are still needed for these tools to be adopted in clinical practice and, ultimately, illustrate

  20. From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction

    Science.gov (United States)

    Drnec, Kim; Marathe, Amar R.; Lukos, Jamie R.; Metcalfe, Jason S.

    2016-01-01

    Human automation interaction (HAI) systems have thus far failed to live up to expectations mainly because human users do not always interact with the automation appropriately. Trust in automation (TiA) has been considered a central influence on the way a human user interacts with an automation; if TiA is too high there will be overuse, if TiA is too low there will be disuse. However, even though extensive research into TiA has identified specific HAI behaviors, or trust outcomes, a unique mapping between trust states and trust outcomes has yet to be clearly identified. Interaction behaviors have been intensely studied in the domain of HAI and TiA and this has led to a reframing of the issues of problems with HAI in terms of reliance and compliance. We find the behaviorally defined terms reliance and compliance to be useful in their functionality for application in real-world situations. However, we note that once an inappropriate interaction behavior has occurred it is too late to mitigate it. We therefore take a step back and look at the interaction decision that precedes the behavior. We note that the decision neuroscience community has revealed that decisions are fairly stereotyped processes accompanied by measurable psychophysiological correlates. Two literatures were therefore reviewed. TiA literature was extensively reviewed in order to understand the relationship between TiA and trust outcomes, as well as to identify gaps in current knowledge. We note that an interaction decision precedes an interaction behavior and believe that we can leverage knowledge of the psychophysiological correlates of decisions to improve joint system performance. As we believe that understanding the interaction decision will be critical to the eventual mitigation of inappropriate interaction behavior, we reviewed the decision making literature and provide a synopsis of the state of the art understanding of the decision process from a decision neuroscience perspective. We forward

  1. From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction.

    Science.gov (United States)

    Drnec, Kim; Marathe, Amar R; Lukos, Jamie R; Metcalfe, Jason S

    2016-01-01

    Human automation interaction (HAI) systems have thus far failed to live up to expectations mainly because human users do not always interact with the automation appropriately. Trust in automation (TiA) has been considered a central influence on the way a human user interacts with an automation; if TiA is too high there will be overuse, if TiA is too low there will be disuse. However, even though extensive research into TiA has identified specific HAI behaviors, or trust outcomes, a unique mapping between trust states and trust outcomes has yet to be clearly identified. Interaction behaviors have been intensely studied in the domain of HAI and TiA and this has led to a reframing of the issues of problems with HAI in terms of reliance and compliance. We find the behaviorally defined terms reliance and compliance to be useful in their functionality for application in real-world situations. However, we note that once an inappropriate interaction behavior has occurred it is too late to mitigate it. We therefore take a step back and look at the interaction decision that precedes the behavior. We note that the decision neuroscience community has revealed that decisions are fairly stereotyped processes accompanied by measurable psychophysiological correlates. Two literatures were therefore reviewed. TiA literature was extensively reviewed in order to understand the relationship between TiA and trust outcomes, as well as to identify gaps in current knowledge. We note that an interaction decision precedes an interaction behavior and believe that we can leverage knowledge of the psychophysiological correlates of decisions to improve joint system performance. As we believe that understanding the interaction decision will be critical to the eventual mitigation of inappropriate interaction behavior, we reviewed the decision making literature and provide a synopsis of the state of the art understanding of the decision process from a decision neuroscience perspective. We forward

  2. Optimizing Decision Preparedness by Adapting Scenario Complexity and Automating Scenario Generation

    Science.gov (United States)

    Dunne, Rob; Schatz, Sae; Flore, Stephen M.; Nicholson, Denise

    2011-01-01

    Klein's recognition-primed decision (RPD) framework proposes that experts make decisions by recognizing similarities between current decision situations and previous decision experiences. Unfortunately, military personnel arQ often presented with situations that they have not experienced before. Scenario-based training (S8T) can help mitigate this gap. However, SBT remains a challenging and inefficient training approach. To address these limitations, the authors present an innovative formulation of scenario complexity that contributes to the larger research goal of developing an automated scenario generation system. This system will enable trainees to effectively advance through a variety of increasingly complex decision situations and experiences. By adapting scenario complexities and automating generation, trainees will be provided with a greater variety of appropriately calibrated training events, thus broadening their repositories of experience. Preliminary results from empirical testing (N=24) of the proof-of-concept formula are presented, and future avenues of scenario complexity research are also discussed.

  3. Fuzzy logic in clinical practice decision support systems

    NARCIS (Netherlands)

    Warren, Jim; Beliakov, Gleb; van der Zwaag, B.J.

    Computerized clinical guidelines can provide significant benefits to health outcomes and costs, however, their effective implementation presents significant problems. Vagueness and ambiguity inherent in natural (textual) clinical guidelines is not readily amenable to formulating automated alerts or

  4. Dialogic Consensus In Clinical Decision-Making.

    Science.gov (United States)

    Walker, Paul; Lovat, Terry

    2016-12-01

    This paper is predicated on the understanding that clinical encounters between clinicians and patients should be seen primarily as inter-relations among persons and, as such, are necessarily moral encounters. It aims to relocate the discussion to be had in challenging medical decision-making situations, including, for example, as the end of life comes into view, onto a more robust moral philosophical footing than is currently commonplace. In our contemporary era, those making moral decisions must be cognizant of the existence of perspectives other than their own, and be attuned to the demands of inter-subjectivity. Applicable to clinical practice, we propose and justify a Habermasian approach as one useful means of achieving what can be described as dialogic consensus. The Habermasian approach builds around, first, his discourse theory of morality as universalizable to all and, second, communicative action as a cooperative search for truth. It is a concrete way to ground the discourse which must be held in complex medical decision-making situations, in its actual reality. Considerations about the theoretical underpinnings of the application of dialogic consensus to clinical practice, and potential difficulties, are explored.

  5. Defining the drivers for accepting decision making automation in air traffic management.

    Science.gov (United States)

    Bekier, Marek; Molesworth, Brett R C; Williamson, Ann

    2011-04-01

    Air Traffic Management (ATM) operators are under increasing pressure to improve the efficiency of their operation to cater for forecasted increases in air traffic movements. One solution involves increasing the utilisation of automation within the ATM system. The success of this approach is contingent on Air Traffic Control Operators' (ATCOs) willingness to accept increased levels of automation. The main aim of the present research was to examine the drivers underpinning ATCOs' willingness to accept increased utilisation of automation within their role. Two fictitious scenarios involving the application of two new automated decision-making tools were created. The results of an online survey revealed traditional predictors of automation acceptance such as age, trust and job satisfaction explain between 4 and 7% of the variance. Furthermore, these predictors varied depending on the purpose in which the automation was to be employed. These results are discussed from an applied and theoretical perspective. STATEMENT OF RELEVANCE: Efficiency improvements in ATM are required to cater for forecasted increases in air traffic movements. One solution is to increase the utilisation of automation within Air Traffic Control. The present research examines the drivers underpinning air traffic controllers' willingness to accept increased levels of automation in their role.

  6. Transformation From a Conventional Clinical Microbiology Laboratory to Full Automation.

    Science.gov (United States)

    Moreno-Camacho, José L; Calva-Espinosa, Diana Y; Leal-Leyva, Yoseli Y; Elizalde-Olivas, Dolores C; Campos-Romero, Abraham; Alcántar-Fernández, Jonathan

    2017-12-22

    To validate the performance, reproducibility, and reliability of BD automated instruments in order to establish a fully automated clinical microbiology laboratory. We used control strains and clinical samples to assess the accuracy, reproducibility, and reliability of the BD Kiestra WCA, the BD Phoenix, and BD Bruker MALDI-Biotyper instruments and compared them to previously established conventional methods. The following processes were evaluated: sample inoculation and spreading, colony counts, sorting of cultures, antibiotic susceptibility test, and microbial identification. The BD Kiestra recovered single colonies in less time than conventional methods (e.g. E. coli, 7h vs 10h, respectively) and agreement between both methodologies was excellent for colony counts (κ=0.824) and sorting cultures (κ=0.821). Antibiotic susceptibility tests performed with BD Phoenix and disk diffusion demonstrated 96.3% agreement with both methods. Finally, we compared microbial identification in BD Phoenix and Bruker MALDI-Biotyper and observed perfect agreement (κ=1) and identification at a species level for control strains. Together these instruments allow us to process clinical urine samples in 36h (effective time). The BD automated technologies have improved performance compared with conventional methods, and are suitable for its implementation in very busy microbiology laboratories. © American Society for Clinical Pathology 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  7. Nurses' Clinical Decision Making on Adopting a Wound Clinical Decision Support System.

    Science.gov (United States)

    Khong, Peck Chui Betty; Hoi, Shu Yin; Holroyd, Eleanor; Wang, Wenru

    2015-07-01

    Healthcare information technology systems are considered the ideal tool to inculcate evidence-based nursing practices. The wound clinical decision support system was built locally to support nurses to manage pressure ulcer wounds in their daily practice. However, its adoption rate is not optimal. The study's objective was to discover the concepts that informed the RNs' decisions to adopt the wound clinical decision support system as an evidence-based technology in their nursing practice. This was an exploratory, descriptive, and qualitative design using face-to-face interviews, individual interviews, and active participatory observation. A purposive, theoretical sample of 14 RNs was recruited from one of the largest public tertiary hospitals in Singapore after obtaining ethics approval. After consenting, the nurses were interviewed and observed separately. Recruitment stopped when data saturation was reached. All transcribed interview data underwent a concurrent thematic analysis, whereas observational data were content analyzed independently and subsequently triangulated with the interview data. Eight emerging themes were identified, namely, use of the wound clinical decision support system, beliefs in the wound clinical decision support system, influences of the workplace culture, extent of the benefits, professional control over nursing practices, use of knowledge, gut feelings, and emotions (fear, doubt, and frustration). These themes represented the nurses' mental outlook as they made decisions on adopting the wound clinical decision support system in light of the complexities of their roles and workloads. This research has provided insight on the nurses' thoughts regarding their decision to interact with the computer environment in a Singapore context. It captured the nurses' complex thoughts when deciding whether to adopt or reject information technology as they practice in a clinical setting.

  8. A distributed clinical decision support system architecture

    Directory of Open Access Journals (Sweden)

    Shaker H. El-Sappagh

    2014-01-01

    Full Text Available This paper proposes an open and distributed clinical decision support system architecture. This technical architecture takes advantage of Electronic Health Record (EHR, data mining techniques, clinical databases, domain expert knowledge bases, available technologies and standards to provide decision-making support for healthcare professionals. The architecture will work extremely well in distributed EHR environments in which each hospital has its own local EHR, and it satisfies the compatibility, interoperability and scalability objectives of an EHR. The system will also have a set of distributed knowledge bases. Each knowledge base will be specialized in a specific domain (i.e., heart disease, and the model achieves cooperation, integration and interoperability between these knowledge bases. Moreover, the model ensures that all knowledge bases are up-to-date by connecting data mining engines to each local knowledge base. These data mining engines continuously mine EHR databases to extract the most recent knowledge, to standardize it and to add it to the knowledge bases. This framework is expected to improve the quality of healthcare, reducing medical errors and guaranteeing the safety of patients by helping clinicians to make correct, accurate, knowledgeable and timely decisions.

  9. Introduction of an automated medical record at an HMO clinic.

    Science.gov (United States)

    Churgin, P G

    1994-01-01

    In May 1993, CIGNA Healthcare of Arizona implemented a comprehensive automated medical record system in a pilot project performed at a primary care clinic in Chandler, Arizona. The system, EpicCare, operates in a client-server environment and completely replaces the paper chart in all phases of medical care. After six months of use by 10 medical providers and a 50-member staff, the system has been approved by clinicians, staff, and patients.

  10. Using the Situated Clinical Decision-Making framework to guide analysis of nurses' clinical decision-making.

    Science.gov (United States)

    Gillespie, Mary

    2010-11-01

    Nurses' clinical decision-making is a complex process that holds potential to influence the quality of care provided and patient outcomes. The evolution of nurses' decision-making that occurs with experience has been well documented. In addition, literature includes numerous strategies and approaches purported to support development of nurses' clinical decision-making. There has been, however, significantly less attention given to the process of assessing nurses' clinical decision-making and novice clinical educators are often challenged with knowing how to best support nurses and nursing students in developing their clinical decision-making capacity. The Situated Clinical Decision-Making framework is presented for use by clinical educators: it provides a structured approach to analyzing nursing students' and novice nurses' decision-making in clinical nursing practice, assists educators in identifying specific issues within nurses' clinical decision-making, and guides selection of relevant strategies to support development of clinical decision-making. A series of questions is offered as a guide for clinical educators when assessing nurses' clinical decision-making. The discussion presents key considerations related to analysis of various decision-making components, including common sources of challenge and errors that may occur within nurses' clinical decision-making. An exemplar illustrates use of the framework and guiding questions. Implications of this approach for selection of strategies that support development of clinical decision-making are highlighted. Copyright © 2010 Elsevier Ltd. All rights reserved.

  11. TUW @ TREC Clinical Decision Support Track

    Science.gov (United States)

    2014-11-01

    and the ShARe/CLEF eHealth Evaluation Lab [8,3] running in 2013 and 2014. Here we briefly describe the goals of the first TREC Clinical Decision...Wendy W. Chapman, David Mart́ınez, Guido Zuccon, and João R. M. Palotti. Overview of the share/clef ehealth evalu- ation lab 2014. In Information Access...Zuccon. Overview of the share/clef ehealth evaluation lab 2013. In Information Access Evaluation. Multilinguality, Multimodality, and Visualization

  12. Automated calculation of ptosis on lateral clinical photographs.

    Science.gov (United States)

    Lee, Juhun; Kim, Edward; Reece, Gregory P; Crosby, Melissa A; Beahm, Elisabeth K; Markey, Mia K

    2015-10-01

    The goal is to fully automate the calculation of a breast ptosis measure from clinical photographs through automatic localization of fiducial points relevant to the measure. Sixty-eight women (97 clinical photographs) who underwent or were scheduled for breast reconstruction were included. The photographs were divided into a development set (N = 49) and an evaluation set (N = 48). The breast ptosis measure is obtained automatically from distances between three fiducial points: the nipple, the lowest visible point of breast (LVP), and the lateral terminus of the inframammary fold (LT). The nipple is localized using the YIQ colour space to highlight the contrast between the areola and the surrounding breast skin. The areola is localized using its shape, location and high Q component intensity. The breast contour is estimated using Dijkstra's shortest path algorithm on the gradient of the photograph in greyscale. The lowest point of the estimated contour is set as the LVP. To locate the anatomically subtle LT, the location of patient's axilla is used as a reference. The algorithm's efficacy was evaluated by comparing manual and automated localizations of the fiducial points. The average nipple diameter was used as a cut-off to define success. The algorithm showed 90, 91 and 83% accuracy for locating the nipple, LVP and LT in the evaluation set, respectively. This study presents a new automated algorithm that may facilitate the quantification of breast ptosis from lateral views of patients' photographs. © 2015 John Wiley & Sons, Ltd.

  13. Pilot interaction with automated airborne decision making systems

    Science.gov (United States)

    Hammer, John M.; Wan, C. Yoon; Vasandani, Vijay

    1987-01-01

    The current research is focused on detection of human error and protection from its consequences. A program for monitoring pilot error by comparing pilot actions to a script was described. It dealt primarily with routine errors (slips) that occurred during checklist activity. The model to which operator actions were compared was a script. Current research is an extension along these two dimensions. The ORS fault detection aid uses a sophisticated device model rather than a script. The newer initiative, the model-based and constraint-based warning system, uses an even more sophisticated device model and is to prevent all types of error, not just slips or bad decision.

  14. Pilot study of a point-of-use decision support tool for cancer clinical trials eligibility.

    Science.gov (United States)

    Breitfeld, P P; Weisburd, M; Overhage, J M; Sledge, G; Tierney, W M

    1999-01-01

    Many adults with cancer are not enrolled in clinical trials because caregivers do not have the time to match the patient's clinical findings with varying eligibility criteria associated with multiple trials for which the patient might be eligible. The authors developed a point-of-use portable decision support tool (DS-TRIEL) to automate this matching process. The support tool consists of a hand-held computer with a programmable relational database. A two-level hierarchic decision framework was used for the identification of eligible subjects for two open breast cancer clinical trials. The hand-held computer also provides protocol consent forms and schemas to further help the busy oncologist. This decision support tool and the decision framework on which it is based could be used for multiple trials and different cancer sites.

  15. Decision support system for outage management and automated crew dispatch

    Science.gov (United States)

    Kang, Ning; Mousavi, Mirrasoul

    2018-01-23

    A decision support system is provided for utility operations to assist with crew dispatch and restoration activities following the occurrence of a disturbance in a multiphase power distribution network, by providing a real-time visualization of possible location(s). The system covers faults that occur on fuse-protected laterals. The system uses real-time data from intelligent electronics devices coupled with other data sources such as static feeder maps to provide a complete picture of the disturbance event, guiding the utility crew to the most probable location(s). This information is provided in real-time, reducing restoration time and avoiding more costly and laborious fault location finding practices.

  16. Automated Decision-Making and Big Data: Concerns for People With Mental Illness.

    Science.gov (United States)

    Monteith, Scott; Glenn, Tasha

    2016-12-01

    Automated decision-making by computer algorithms based on data from our behaviors is fundamental to the digital economy. Automated decisions impact everyone, occurring routinely in education, employment, health care, credit, and government services. Technologies that generate tracking data, including smartphones, credit cards, websites, social media, and sensors, offer unprecedented benefits. However, people are vulnerable to errors and biases in the underlying data and algorithms, especially those with mental illness. Algorithms based on big data from seemingly unrelated sources may create obstacles to community integration. Voluntary online self-disclosure and constant tracking blur traditional concepts of public versus private data, medical versus non-medical data, and human versus automated decision-making. In contrast to sharing sensitive information with a physician in a confidential relationship, there may be numerous readers of information revealed online; data may be sold repeatedly; used in proprietary algorithms; and are effectively permanent. Technological changes challenge traditional norms affecting privacy and decision-making, and continued discussions on new approaches to provide privacy protections are needed.

  17. Automated blood-sample handling in the clinical laboratory.

    Science.gov (United States)

    Godolphin, W; Bodtker, K; Uyeno, D; Goh, L O

    1990-09-01

    The only significant advances in blood-taking in 25 years have been the disposable needle and evacuated blood-drawing tube. With the exception of a few isolated barcode experiments, most sample-tracking is performed through handwritten or computer-printed labels. Attempts to reduce the hazards of centrifugation have resulted in air-tight lids or chambers, the use of which is time-consuming and cumbersome. Most commonly used clinical analyzers require serum or plasma, distributed into specialized containers, unique to that analyzer. Aliquots for different tests are prepared by handpouring or pipetting. Moderate to large clinical laboratories perform so many different tests that even multi-analyzers performing multiple analyses on a single sample may account for only a portion of all tests ordered for a patient. Thus several aliquots of each specimen are usually required. We have developed a proprietary serial centrifuge and blood-collection tube suitable for incorporation into an automated or robotic sample-handling system. The system we propose is (a) safe--avoids or prevents biological danger to the many "handlers" of blood; (b) small--minimizes the amount of sample taken and space required to adapt to the needs of satellite and mobile testing, and direct interfacing with analyzers; (c) serial--permits each sample to be treated according to its own "merits," optimizes throughput, and facilitates flexible automation; and (d) smart--ensures quality results through monitoring and intelligent control of patient identification, sample characteristics, and separation process.

  18. Amsterdam wrist rules: A clinical decision aid

    Directory of Open Access Journals (Sweden)

    Bentohami Abdelali

    2011-10-01

    Full Text Available Abstract Background Acute trauma of the wrist is one of the most frequent reasons for visiting the Emergency Department. These patients are routinely referred for radiological examination. Most X-rays however, do not reveal any fractures. A clinical decision rule determining the need for X-rays in patients with acute wrist trauma may help to percolate and select patients with fractures. Methods/Design This study will be a multi-center observational diagnostic study in which the data will be collected cross-sectionally. The study population will consist of all consecutive adult patients (≥18 years presenting with acute wrist trauma at the Emergency Department in the participating hospitals. This research comprises two components: one study will be conducted to determine which clinical parameters are predictive for the presence of a distal radius fracture in adult patients presenting to the Emergency Department following acute wrist trauma. These clinical parameters are defined by trauma-mechanism, physical examination, and functional testing. This data will be collected in two of the three participating hospitals and will be assessed by using logistic regression modelling to estimate the regression coefficients after which a reduced model will be created by means of a log likelihood ratio test. The accuracy of the model will be estimated by a goodness of fit test and an ROC curve. The final model will be validated internally through bootstrapping and by shrinking it, an adjusted model will be generated. In the second component of this study, the developed prediction model will be validated in a new dataset consisting of a population of patients from the third hospital. If necessary, the model will be calibrated using the data from the validation study. Discussion Wrist trauma is frequently encountered at the Emergency Department. However, to this date, no decision rule regarding this type of trauma has been created. Ideally, radiographs are

  19. Automated syndrome detection in a set of clinical facial photographs.

    Science.gov (United States)

    Boehringer, Stefan; Guenther, Manuel; Sinigerova, Stella; Wurtz, Rolf P; Horsthemke, Bernhard; Wieczorek, Dagmar

    2011-09-01

    Computer systems play an important role in clinical genetics and are a routine part of finding clinical diagnoses but make it difficult to fully exploit information derived from facial appearance. So far, automated syndrome diagnosis based on digital, facial photographs has been demonstrated under study conditions but has not been applied in clinical practice. We have therefore investigated how well statistical classifiers trained on study data comprising 202 individuals affected by one of 14 syndromes could classify a set of 91 patients for whom pictures were taken under regular, less controlled conditions in clinical practice. We found a classification accuracy of 21% percent in the clinical sample representing a ratio of 3.0 over a random choice. This contrasts with a 60% accuracy or 8.5 ratio in the training data. Producing average images in both groups from sets of pictures for each syndrome demonstrates that the groups exhibit large phenotypic differences explaining discrepancies in accuracy. A broadening of the data set is suggested in order to improve accuracy in clinical practice. In order to further this goal, a software package is made available that allows application of the procedures and contributions toward an improved data set. Copyright © 2011 Wiley-Liss, Inc.

  20. Clinical Decision Support Tools: The Evolution of a Revolution

    NARCIS (Netherlands)

    Mould, D. R.; D'Haens, G.; Upton, R. N.

    2016-01-01

    Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug

  1. Failsafe automation of Phase II clinical trial interim monitoring for stopping rules.

    Science.gov (United States)

    Day, Roger S

    2010-02-01

    In Phase II clinical trials in cancer, preventing the treatment of patients on a study when current data demonstrate that the treatment is insufficiently active or too toxic has obvious benefits, both in protecting patients and in reducing sponsor costs. Considerable efforts have gone into experimental designs for Phase II clinical trials with flexible sample size, usually implemented by early stopping rules. The intended benefits will not ensue, however, if the design is not followed. Despite the best intentions, failures can occur for many reasons. The main goal is to develop an automated system for interim monitoring, as a backup system supplementing the protocol team, to ensure that patients are protected. A secondary goal is to stimulate timely recording of patient assessments. We developed key concepts and performance needs, then designed, implemented, and deployed a software solution embedded in the clinical trials database system. The system has been in place since October 2007. One clinical trial tripped the automated monitor, resulting in e-mails that initiated statistician/investigator review in timely fashion. Several essential contributing activities still require human intervention, institutional policy decisions, and institutional commitment of resources. We believe that implementing the concepts presented here will provide greater assurance that interim monitoring plans are followed and that patients are protected from inadequate response or excessive toxicity. This approach may also facilitate wider acceptance and quicker implementation of new interim monitoring algorithms.

  2. Development of an Automated Decision-Making Tool for Supervisory Control System

    Energy Technology Data Exchange (ETDEWEB)

    Cetiner, Sacit M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Muhlheim, Michael David [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Flanagan, George F. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Fugate, David L. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kisner, Roger A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2014-09-01

    This technical report was generated as a product of the Supervisory Control for Multi-Modular Small Modular Reactor (SMR) Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (AdvSMR) Research and Development Program of the US Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular AdvSMR plants. This research activity advances the state of the art by incorporating real-time, probabilistic-based decision-making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides background information on the state of the art of automated decision-making, including the description of existing methodologies. It then presents a description of a generalized decision-making framework, upon which the supervisory control decision-making algorithm is based. The probabilistic portion of automated decision-making is demonstrated through a simple hydraulic loop example.

  3. Automated Clinical Assessment from Smart home-based Behavior Data

    Science.gov (United States)

    Dawadi, Prafulla Nath; Cook, Diane Joyce; Schmitter-Edgecombe, Maureen

    2016-01-01

    Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behaviour in the home and predicting standard clinical assessment scores of the residents. To accomplish this goal, we propose a Clinical Assessment using Activity Behavior (CAAB) approach to model a smart home resident’s daily behavior and predict the corresponding standard clinical assessment scores. CAAB uses statistical features that describe characteristics of a resident’s daily activity performance to train machine learning algorithms that predict the clinical assessment scores. We evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years using prediction and classification-based experiments. In the prediction-based experiments, we obtain a statistically significant correlation (r = 0.72) between CAAB-predicted and clinician-provided cognitive assessment scores and a statistically significant correlation (r = 0.45) between CAAB-predicted and clinician-provided mobility scores. Similarly, for the classification-based experiments, we find CAAB has a classification accuracy of 72% while classifying cognitive assessment scores and 76% while classifying mobility scores. These prediction and classification results suggest that it is feasible to predict standard clinical scores using smart home sensor data and learning-based data analysis. PMID:26292348

  4. Conceptualising a system for quality clinical decision-making in ...

    African Journals Online (AJOL)

    As a feedback mechanism to promote or improve the quality of clinical decisions in nursing, standards for quality clinical decision-making are proposed in an exemplary manner. In addition, a system for quality clinical decisionmaking in nursing capitalises on the heritage of the nursing process. Considering the changes and ...

  5. Decaying relevance of clinical data towards future decisions in data-driven inpatient clinical order sets.

    Science.gov (United States)

    Chen, Jonathan H; Alagappan, Muthuraman; Goldstein, Mary K; Asch, Steven M; Altman, Russ B

    2017-06-01

    Determine how varying longitudinal historical training data can impact prediction of future clinical decisions. Estimate the "decay rate" of clinical data source relevance. We trained a clinical order recommender system, analogous to Netflix or Amazon's "Customers who bought A also bought B..." product recommenders, based on a tertiary academic hospital's structured electronic health record data. We used this system to predict future (2013) admission orders based on different subsets of historical training data (2009 through 2012), relative to existing human-authored order sets. Predicting future (2013) inpatient orders is more accurate with models trained on just one month of recent (2012) data than with 12 months of older (2009) data (ROC AUC 0.91 vs. 0.88, precision 27% vs. 22%, recall 52% vs. 43%, all P<10 -10 ). Algorithmically learned models from even the older (2009) data was still more effective than existing human-authored order sets (ROC AUC 0.81, precision 16% recall 35%). Training with more longitudinal data (2009-2012) was no better than using only the most recent (2012) data, unless applying a decaying weighting scheme with a "half-life" of data relevance about 4 months. Clinical practice patterns (automatically) learned from electronic health record data can vary substantially across years. Gold standards for clinical decision support are elusive moving targets, reinforcing the need for automated methods that can adapt to evolving information. Prioritizing small amounts of recent data is more effective than using larger amounts of older data towards future clinical predictions. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  6. An online infertility clinical decision support system

    Directory of Open Access Journals (Sweden)

    Fabio Diniz de Souza

    2017-01-01

    Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system.Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool's output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (χ2 test with Yates' correction for continuity (P<0.05 was performed to verify if the online tool's and the doctor's diagnoses were statistically associated with the final diagnoses.Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool's performance for that factor.Conclusions: The online tool tends to present more false-positives than false-negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.

  7. An online infertility clinical decision support system

    Directory of Open Access Journals (Sweden)

    Fabio Diniz de Souza

    2017-09-01

    Full Text Available Objective: To explore some possibilities of computer applications in medicine, and to discuss an online infertility clinical decision support system. Methods: Retrospective data were obtained from 52 couples, and then entered into the online tool. Both its results and the initial diagnoses obtained by the treating physicians were compared with the final diagnoses established by laparoscopy and other diagnostic tests (semen analysis, hormone analysis, endometrial biopsy, ultrasound and hysteroscopy. The initial hypothesis of the research was that the online tool’s output was statistically associated with the final diagnoses. In order to verify that hypothesis, a chi-square (氈2 test with Yates’ correction for continuity (P<0.05 was performed to verify if the online tool’s and the doctor’s diagnoses were statistically associated with the final diagnoses. Results: Four etiological factors were present in more than 50% of the couples (ovarian, tubal-peritoneal, uterine, and endometriosis. The statistical results confirmed the research hypothesis for eight out of the nine etiological factors (ovarian, tubal-peritoneal, uterine, cervical, male, vaginal, psychosomatic, and endometriosis; P<0.05. Since there were no cases related to the immune factor in the sample, further clinical data are necessary in order to assess the online tool’s performance for that factor. Conclusions: The online tool tends to present more false-positives than false negatives, whereas the expert physician tends to present more false-negatives than false-positives. Therefore, the online tool and the doctor seem to complement each other. Finally, the obtained results suggest that the infertility online tool discussed herein might be a useful research and instructional tool.

  8. Clinical decision regret among critical care nurses: a qualitative analysis.

    Science.gov (United States)

    Arslanian-Engoren, Cynthia; Scott, Linda D

    2014-01-01

    Decision regret is a negative cognitive emotion associated with experiences of guilt and situations of interpersonal harm. These negative affective responses may contribute to emotional exhaustion in critical care nurses (CCNs), increased staff turnover rates and high medication error rates. Yet, little is known about clinical decision regret among CCNs or the conditions or situations (e.g., feeling sleepy) that may precipitate its occurrence. To examine decision regret among CCNs, with an emphasis on clinical decisions made when nurses were most sleepy. A content analytic approach was used to examine the narrative descriptions of clinical decisions by CCNs when sleepy. Six decision regret themes emerged that represented deviations in practice or performance behaviors that were attributed to fatigued CCNs. While 157 CCNs disclosed a clinical decision they made at work while sleepy, the prevalence may be underestimated and warrants further investigation. Copyright © 2014 Elsevier Inc. All rights reserved.

  9. A service oriented approach for guidelines-based clinical decision support using BPMN.

    Science.gov (United States)

    Rodriguez-Loya, Salvador; Aziz, Ayesha; Chatwin, Chris

    2014-01-01

    Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS).

  10. Intelligent Case Based Decision Support System for Online Diagnosis of Automated Production System

    International Nuclear Information System (INIS)

    Ben Rabah, N; Saddem, R; Carre-Menetrier, V; Ben Hmida, F; Tagina, M

    2017-01-01

    Diagnosis of Automated Production System (APS) is a decision-making process designed to detect, locate and identify a particular failure caused by the control law. In the literature, there are three major types of reasoning for industrial diagnosis: the first is model-based, the second is rule-based and the third is case-based. The common and major limitation of the first and the second reasonings is that they do not have automated learning ability. This paper presents an interactive and effective Case Based Decision Support System for online Diagnosis (CB-DSSD) of an APS. It offers a synergy between the Case Based Reasoning (CBR) and the Decision Support System (DSS) in order to support and assist Human Operator of Supervision (HOS) in his/her decision process. Indeed, the experimental evaluation performed on an Interactive Training System for PLC (ITS PLC) that allows the control of a Programmable Logic Controller (PLC), simulating sensors or/and actuators failures and validating the control algorithm through a real time interactive experience, showed the efficiency of our approach. (paper)

  11. How to make the best decision. Philosophical aspects of clinical decision theory.

    Science.gov (United States)

    Wulff, H R

    1981-01-01

    An attempt is made to discuss some of the philosophical implications of the use of decision-analytic techniques. The probabilities of a decision analysis are subjective measures of belief, and it is concluded that clinicians base their subjective beliefs on both recorded observations and theoretical knowledge. The clinical decision maker also evaluates the consequences of his actions, and therefore clinical decision theory transcends medical science. A number of different schools of normative ethics are mentioned to illustrate the complexity of everyday decision making. The philosophical terminology is useful for the analysis of clinical problems, and it is argued that clinical decision making has both a teleological and a deontological component. The results of decision-analytic studies depend on such factors as the wealth of the country, the organization of the health service, and cultural norms.

  12. Decision analysis in the clinical neurosciences

    NARCIS (Netherlands)

    D.W.J. Dippel (Diederik)

    1994-01-01

    textabstractDiagnostic and therapeutic choice in neurology can fortunately be made without formal decision support in the majority of cases. in many patients a diagnosis and treatment choice are relatively easy to establish. This study however, concerns the application of a decision support

  13. Automation of information decision support to improve e-learning resources quality

    Directory of Open Access Journals (Sweden)

    A.L. Danchenko

    2013-06-01

    Full Text Available Purpose. In conditions of active development of e-learning the high quality of e-learning resources is very important. Providing the high quality of e-learning resources in situation with mass higher education and rapid obsolescence of information requires the automation of information decision support for improving the quality of e-learning resources by development of decision support system. Methodology. The problem is solved by methods of artificial intelligence. The knowledge base of information structure of decision support system that is based on frame model of knowledge representation and inference production rules are developed. Findings. According to the results of the analysis of life cycle processes and requirements to the e-learning resources quality the information model of the structure of the knowledge base of the decision support system, the inference rules for the automatically generating of recommendations and the software implementation are developed. Practical value. It is established that the basic requirements for quality are performance, validity, reliability and manufacturability. It is shown that the using of a software implementation of decision support system for researched courses gives a growth of the quality according to the complex quality criteria. The information structure of a knowledge base system to support decision-making and rules of inference can be used by methodologists and content developers of learning systems.

  14. Heuristics in Managing Complex Clinical Decision Tasks in Experts' Decision Making.

    Science.gov (United States)

    Islam, Roosan; Weir, Charlene; Del Fiol, Guilherme

    2014-09-01

    Clinical decision support is a tool to help experts make optimal and efficient decisions. However, little is known about the high level of abstractions in the thinking process for the experts. The objective of the study is to understand how clinicians manage complexity while dealing with complex clinical decision tasks. After approval from the Institutional Review Board (IRB), three clinical experts were interviewed the transcripts from these interviews were analyzed. We found five broad categories of strategies by experts for managing complex clinical decision tasks: decision conflict, mental projection, decision trade-offs, managing uncertainty and generating rule of thumb. Complexity is created by decision conflicts, mental projection, limited options and treatment uncertainty. Experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes and focusing on only the most relevant information. Understanding complex decision making processes can help design allocation based on the complexity of task for clinical decision support design.

  15. Clinical Decision Making of Nurses Working in Hospital Settings

    OpenAIRE

    Ida Torunn Bjørk; Glenys A. Hamilton

    2011-01-01

    This study analyzed nurses' perceptions of clinical decision making (CDM) in their clinical practice and compared differences in decision making related to nurse demographic and contextual variables. A cross-sectional survey was carried out with 2095 nurses in four hospitals in Norway. A 24-item Nursing Decision Making Instrument based on cognitive continuum theory was used to explore how nurses perceived their CDM when meeting an elective patient for the first time. Data were analyzed with d...

  16. The Pedagogical Reflection Model - an educational perspective on clinical decisions

    DEFF Research Database (Denmark)

    Voergaard Poulsen, Bettina; Vibholm Persson, Stine; Skriver, Mette

    Clinical decision-making is important in patient-centred nursing, which is known in nursing education and research (1) The Pedagogical Reflection Model (PRM) can provide a framework that supports students’ decision-making in patient-specific situations. PRM is based on the assumption that clinical......) The aims of this study were to explore how nurse students and clinical supervisors use PRM as method to reflect before, during and after PRM guidance in relation to clinical decisions in the first year of clinical practice...... decision-making needs to take into account; 1) clinical experiences, 2) the perspective of the patient, 3) clinical observations and investigations, 4) knowledge about patients experiences of being a patient and ill, 5) medical knowledge about diseases, and 6) the organizational framework (2,3,4)(Figure 1...

  17. Automated detection of actinic keratoses in clinical photographs.

    Science.gov (United States)

    Hames, Samuel C; Sinnya, Sudipta; Tan, Jean-Marie; Morze, Conrad; Sahebian, Azadeh; Soyer, H Peter; Prow, Tarl W

    2015-01-01

    Clinical diagnosis of actinic keratosis is known to have intra- and inter-observer variability, and there is currently no non-invasive and objective measure to diagnose these lesions. The aim of this pilot study was to determine if automatically detecting and circumscribing actinic keratoses in clinical photographs is feasible. Photographs of the face and dorsal forearms were acquired in 20 volunteers from two groups: the first with at least on actinic keratosis present on the face and each arm, the second with no actinic keratoses. The photographs were automatically analysed using colour space transforms and morphological features to detect erythema. The automated output was compared with a senior consultant dermatologist's assessment of the photographs, including the intra-observer variability. Performance was assessed by the correlation between total lesions detected by automated method and dermatologist, and whether the individual lesions detected were in the same location as the dermatologist identified lesions. Additionally, the ability to limit false positives was assessed by automatic assessment of the photographs from the no actinic keratosis group in comparison to the high actinic keratosis group. The correlation between the automatic and dermatologist counts was 0.62 on the face and 0.51 on the arms, compared to the dermatologist's intra-observer variation of 0.83 and 0.93 for the same. Sensitivity of automatic detection was 39.5% on the face, 53.1% on the arms. Positive predictive values were 13.9% on the face and 39.8% on the arms. Significantly more lesions (p<0.0001) were detected in the high actinic keratosis group compared to the no actinic keratosis group. The proposed method was inferior to assessment by the dermatologist in terms of sensitivity and positive predictive value. However, this pilot study used only a single simple feature and was still able to achieve sensitivity of detection of 53.1% on the arms.This suggests that image analysis is

  18. Automated Extraction of Substance Use Information from Clinical Texts.

    Science.gov (United States)

    Wang, Yan; Chen, Elizabeth S; Pakhomov, Serguei; Arsoniadis, Elliot; Carter, Elizabeth W; Lindemann, Elizabeth; Sarkar, Indra Neil; Melton, Genevieve B

    2015-01-01

    Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus. The system attained F-scores of 89.8, 84.6 and 89.4 respectively for alcohol, drug, and nicotine use statement detection, as well as average F-scores of 82.1, 90.3, 80.8, 88.7, 96.6, and 74.5 respectively for extraction of attributes. Our results suggest that NLP systems can achieve good performance when augmented with linguistic resources and domain knowledge when applied to a wide breadth of substance use free text clinical notes.

  19. Decision-making and problem-solving methods in automation technology

    Science.gov (United States)

    Hankins, W. W.; Pennington, J. E.; Barker, L. K.

    1983-01-01

    The state of the art in the automation of decision making and problem solving is reviewed. The information upon which the report is based was derived from literature searches, visits to university and government laboratories performing basic research in the area, and a 1980 Langley Research Center sponsored conferences on the subject. It is the contention of the authors that the technology in this area is being generated by research primarily in the three disciplines of Artificial Intelligence, Control Theory, and Operations Research. Under the assumption that the state of the art in decision making and problem solving is reflected in the problems being solved, specific problems and methods of their solution are often discussed to elucidate particular aspects of the subject. Synopses of the following major topic areas comprise most of the report: (1) detection and recognition; (2) planning; and scheduling; (3) learning; (4) theorem proving; (5) distributed systems; (6) knowledge bases; (7) search; (8) heuristics; and (9) evolutionary programming.

  20. Profiling and Automated Decision Making in the Present and New EU Data Protection Frameworks

    DEFF Research Database (Denmark)

    Savin, Andrej

    The digital world of the 21st century is increasingly the world of automatic decision making. In such a world, an ever larger number of tasks are relegated to computers which gather and process data as well as suggest or make decisions silently and with little supervision. This situation has been...... made possible by a transfer of a staggering portion of our daily lives from the offline world to the Internet. It is a truism that automation would be impossible without our willing participation on the Internet. We freely take part in social networks, post on blogs, and send our emails. On the other...... hand, it is equally true that we are increasingly monitored by the state, by profit‐maximizing corporations and by our fellow citizens and that these methods of monitoring are becoming smarter. Vast amounts of data which have become available and which we contribute, form what we today call “big data...

  1. Ethical decision making in clinical practice.

    Science.gov (United States)

    Fowler, M D

    1989-12-01

    Contemporary nursing ethics education focuses on the use of an analytical model of ethical decision making for both its process and its content. Perhaps this is the case because it bears some resemblance to the nursing process, which is taught in a similar fashion. Thus, a deductivist method of ethical decision making fits within the same general schema of the hypotheticodeductive method of decision making that is taught for nursing diagnosis. Ethics requires that nurses respect persons, inform patients and secure their consent, not inflict harm, preserve the patient's quality of life, prevent harm and remove harmful conditions, do good for patients, and minimize risk to themselves. These are among the norms of obligation that guide ethical analysis and judgment in nursing practice and are the substance of the analytical model of ethical decision making. Nursing's ethics has established high ideals and strong demands for nurses. These are demands which nurses have met and ideals which have often been realized. Whatever the strength of our science, nursing is an inherently moral endeavor and is only as strong as its commitment to its ethical obligations and values. Between the grinding edges of the forces that affect it, nursing must establish its priorities among the aspects of its environment that it attempts to control. Ethics must be chief among those priorities.

  2. Clinical Decision Support: Statistical Hopes and Challenges

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2016-01-01

    Roč. 4, č. 1 (2016), s. 30-34 ISSN 1805-8698 Grant - others:Nadační fond na opdporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : decision support * data mining * multivariate statistics * psychiatry * information based medicine Subject RIV: BB - Applied Statistics, Operational Research

  3. Automated Segmentation of Coronary Arteries Based on Statistical Region Growing and Heuristic Decision Method

    Directory of Open Access Journals (Sweden)

    Yun Tian

    2016-01-01

    Full Text Available The segmentation of coronary arteries is a vital process that helps cardiovascular radiologists detect and quantify stenosis. In this paper, we propose a fully automated coronary artery segmentation from cardiac data volume. The method is built on a statistics region growing together with a heuristic decision. First, the heart region is extracted using a multi-atlas-based approach. Second, the vessel structures are enhanced via a 3D multiscale line filter. Next, seed points are detected automatically through a threshold preprocessing and a subsequent morphological operation. Based on the set of detected seed points, a statistics-based region growing is applied. Finally, results are obtained by setting conservative parameters. A heuristic decision method is then used to obtain the desired result automatically because parameters in region growing vary in different patients, and the segmentation requires full automation. The experiments are carried out on a dataset that includes eight-patient multivendor cardiac computed tomography angiography (CTA volume data. The DICE similarity index, mean distance, and Hausdorff distance metrics are employed to compare the proposed algorithm with two state-of-the-art methods. Experimental results indicate that the proposed algorithm is capable of performing complete, robust, and accurate extraction of coronary arteries.

  4. Critical care nurse practitioners and clinical nurse specialists interface patterns with computer-based decision support systems.

    Science.gov (United States)

    Weber, Scott

    2007-11-01

    The purposes of this review are to examine the types of clinical decision support systems in use and to identify patterns of how critical care advanced practice nurses (APNs) have integrated these systems into their nursing care patient management practices. The decision-making process itself is analyzed with a focus on how automated systems attempt to capture and reflect human decisional processes in critical care nursing, including how systems actually organize and process information to create outcome estimations based on patient clinical indicators and prognosis logarithms. Characteristics of APN clinicians and implications of these characteristics on decision system use, based on the body of decision system user research, are introduced. A review of the Medline, Ovid, CINAHL, and PubMed literature databases was conducted using "clinical decision support systems,"computerized clinical decision making," and "APNs"; an examination of components of several major clinical decision systems was also undertaken. Use patterns among APNs and other clinicians appear to vary; there is a need for original research to examine how APNs actually use these systems in their practices in critical care settings. Because APNs are increasingly responsible for admission to, and transfer from, critical care settings, more understanding is needed on how they interact with this technology and how they see automated decision systems impacting their practices. APNs who practice in critical care settings vary significantly in how they use the clinical decision systems that are in operation in their practice settings. These APNs must have an understanding of their use patterns with these systems and should critically assess whether their patient care decision making is affected by the technology.

  5. Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

    International Nuclear Information System (INIS)

    Hargrave, C; Deegan, T; Gibbs, A; Poulsen, M; Moores, M; Harden, F; Mengersen, K

    2014-01-01

    A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

  6. Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

    Science.gov (United States)

    Hargrave, C.; Moores, M.; Deegan, T.; Gibbs, A.; Poulsen, M.; Harden, F.; Mengersen, K.

    2014-03-01

    A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific subregions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

  7. Decision aids for people considering taking part in clinical trials.

    Science.gov (United States)

    Gillies, Katie; Cotton, Seonaidh C; Brehaut, Jamie C; Politi, Mary C; Skea, Zoe

    2015-11-27

    Several interventions have been developed to promote informed consent for participants in clinical trials. However, many of these interventions focus on the content and structure of information (e.g. enhanced information or changes to the presentation format) rather than the process of decision making. Patient decision aids support a decision making process about medical options. Decision aids support the decision process by providing information about available options and their associated outcomes, alongside information that enables patients to consider what value they place on particular outcomes, and provide structured guidance on steps of decision making. They have been shown to be effective for treatment and screening decisions but evidence on their effectiveness in the context of informed consent for clinical trials has not been synthesised. To assess the effectiveness of decision aids for clinical trial informed consent compared to no intervention, standard information (i.e. usual practice) or an alternative intervention on the decision making process. We searched the following databases and to March 2015: Cochrane Central Register of Controlled Trials (CENTRAL), The Cochrane Library; MEDLINE (OvidSP) (from 1950); EMBASE (OvidSP) (from 1980); PsycINFO (OvidSP) (from 1806); ASSIA (ProQuest) (from 1987); WHO International Clinical Trials Registry Platform (ICTRP) (http://apps.who.int/trialsearch/); ClinicalTrials.gov; ISRCTN Register (http://www.controlled-trials.com/isrctn/). We also searched reference lists of included studies and relevant reviews. We contacted study authors and other experts. There were no language restrictions. We included randomised and quasi-randomised controlled trials comparing decision aids in the informed consent process for clinical trials alone, or in conjunction with standard information (such as written or verbal) or alongside alternative interventions (e.g. paper-based versus web-based decision aids). Included trials involved

  8. Clinical decision-making: physicians' preferences and experiences

    Directory of Open Access Journals (Sweden)

    White Martha

    2007-03-01

    Full Text Available Abstract Background Shared decision-making has been advocated; however there are relatively few studies on physician preferences for, and experiences of, different styles of clinical decision-making as most research has focused on patient preferences and experiences. The objectives of this study were to determine 1 physician preferences for different styles of clinical decision-making; 2 styles of clinical decision-making physicians perceive themselves as practicing; and 3 the congruence between preferred and perceived style. In addition we sought to determine physician perceptions of the availability of time in visits, and their role in encouraging patients to look for health information. Methods Cross-sectional survey of a nationally representative sample of U.S. physicians. Results 1,050 (53% response rate physicians responded to the survey. Of these, 780 (75% preferred to share decision-making with their patients, 142 (14% preferred paternalism, and 118 (11% preferred consumerism. 87% of physicians perceived themselves as practicing their preferred style. Physicians who preferred their patients to play an active role in decision-making were more likely to report encouraging patients to look for information, and to report having enough time in visits. Conclusion Physicians tend to perceive themselves as practicing their preferred role in clinical decision-making. The direction of the association cannot be inferred from these data; however, we suggest that interventions aimed at promoting shared decision-making need to target physicians as well as patients.

  9. E-health, phase two: the imperative to integrate process automation with communication automation for large clinical reference laboratories.

    Science.gov (United States)

    White, L; Terner, C

    2001-01-01

    The initial efforts of e-health have fallen far short of expectations. They were buoyed by the hype and excitement of the Internet craze but limited by their lack of understanding of important market and environmental factors. E-health now recognizes that legacy systems and processes are important, that there is a technology adoption process that needs to be followed, and that demonstrable value drives adoption. Initial e-health transaction solutions have targeted mostly low-cost problems. These solutions invariably are difficult to integrate into existing systems, typically requiring manual interfacing to supported processes. This limitation in particular makes them unworkable for large volume providers. To meet the needs of these providers, e-health companies must rethink their approaches, appropriately applying technology to seamlessly integrate all steps into existing business functions. E-automation is a transaction technology that automates steps, integration of steps, and information communication demands, resulting in comprehensive automation of entire business functions. We applied e-automation to create a billing management solution for clinical reference laboratories. Large volume, onerous regulations, small margins, and only indirect access to patients challenge large laboratories' billing departments. Couple these problems with outmoded, largely manual systems and it becomes apparent why most laboratory billing departments are in crisis. Our approach has been to focus on the most significant and costly problems in billing: errors, compliance, and system maintenance and management. The core of the design relies on conditional processing, a "universal" communications interface, and ASP technologies. The result is comprehensive automation of all routine processes, driving out errors and costs. Additionally, compliance management and billing system support and management costs are dramatically reduced. The implications of e-automated processes can extend

  10. About the methodology of system synthesis of decision-makings and its procedures automation

    Directory of Open Access Journals (Sweden)

    D. P. Oleynikov

    2016-01-01

     the use of computer equipment, which require signifi cant time expenses on the development of appropriate solutions. Therefore, it was decided to develop an automated system to improve the effectiveness of the implementation of a number of methodology procedures.Results.During the study were identifi ed use cases of the system, in accordance with which were formed the conceptual and technical architecture of the system, highlights the key subsystems of the reference data, knowledge about the methods of decision-making and synthesis strategies, and identifi es their development tools. As the database used by the DBMS MS SQL Server, as the client side – Borland Delphi.Conclusion. Due to the high complexity of formalization of intellectual, creative, methodologies operations, the focus of automation is the support of conceptual analysis of the decisionmakings subject area and formation on its basis the knowledge base of intellectual operations together with their characteristic features, aimed to combine operations that make up the group of methods of synthesis strategies decision-making and implementation of the search function on the basis of a intellectual operations knowledge base.

  11. An exploration of clinical decision making in mental health triage.

    Science.gov (United States)

    Sands, Natisha

    2009-08-01

    Mental health (MH) triage is a specialist area of clinical nursing practice that involves complex decision making. The discussion in this article draws on the findings of a Ph.D. study that involved a statewide investigation of the scope of MH triage nursing practice in Victoria, Australia. Although the original Ph.D. study investigated a number of core practices in MH triage, the focus of the discussion in this article is specifically on the findings related to clinical decision making in MH triage, which have not previously been published. The study employed an exploratory descriptive research design that used mixed data collection methods including a survey questionnaire (n = 139) and semistructured interviews (n = 21). The study findings related to decision making revealed a lack of empirically tested evidence-based decision-making frameworks currently in use to support MH triage nursing practice. MH triage clinicians in Australia rely heavily on clinical experience to underpin decision making and have little of knowledge of theoretical models for practice, such as methodologies for rating urgency. A key recommendation arising from the study is the need to develop evidence-based decision-making frameworks such as clinical guidelines to inform and support MH triage clinical decision making.

  12. The impact of simulation sequencing on perceived clinical decision making.

    Science.gov (United States)

    Woda, Aimee; Hansen, Jamie; Paquette, Mary; Topp, Robert

    2017-09-01

    An emerging nursing education trend is to utilize simulated learning experiences as a means to optimize competency and decision making skills. The purpose of this study was to examine differences in students' perception of clinical decision making and clinical decision making-related self-confidence and anxiety based on the sequence (order) in which they participated in a block of simulated versus hospital-based learning experiences. A quasi-experimental crossover design was used. Between and within group differences were found relative to self-confidence with the decision making process. When comparing groups, at baseline the simulation followed by hospital group had significantly higher self-confidence scores, however, at 14-weeks both groups were not significantly different. Significant within group differences were found in the simulation followed by hospital group only, demonstrating a significant decrease in clinical decision making related anxiety across the semester. Finally, there were no significant difference in; perceived clinical decision making within or between the groups at the two measurement points. Preliminary findings suggest that simulated learning experiences can be offered with alternating sequences without impacting the process, anxiety or confidence with clinical decision making. This study provides beginning evidence to guide curriculum development and allow flexibility based on student needs and available resources. Copyright © 2017. Published by Elsevier Ltd.

  13. Bayesian networks for clinical decision support: A rational approach to dynamic decision-making under uncertainty

    NARCIS (Netherlands)

    Gerven, M.A.J. van

    2007-01-01

    This dissertation deals with decision support in the context of clinical oncology. (Dynamic) Bayesian networks are used as a framework for (dynamic) decision-making under uncertainty and applied to a variety of diagnostic, prognostic, and treatment problems in medicine. It is shown that the proposed

  14. A novel approach to sequence validating protein expression clones with automated decision making

    Directory of Open Access Journals (Sweden)

    Mohr Stephanie E

    2007-06-01

    Full Text Available Abstract Background Whereas the molecular assembly of protein expression clones is readily automated and routinely accomplished in high throughput, sequence verification of these clones is still largely performed manually, an arduous and time consuming process. The ultimate goal of validation is to determine if a given plasmid clone matches its reference sequence sufficiently to be "acceptable" for use in protein expression experiments. Given the accelerating increase in availability of tens of thousands of unverified clones, there is a strong demand for rapid, efficient and accurate software that automates clone validation. Results We have developed an Automated Clone Evaluation (ACE system – the first comprehensive, multi-platform, web-based plasmid sequence verification software package. ACE automates the clone verification process by defining each clone sequence as a list of multidimensional discrepancy objects, each describing a difference between the clone and its expected sequence including the resulting polypeptide consequences. To evaluate clones automatically, this list can be compared against user acceptance criteria that specify the allowable number of discrepancies of each type. This strategy allows users to re-evaluate the same set of clones against different acceptance criteria as needed for use in other experiments. ACE manages the entire sequence validation process including contig management, identifying and annotating discrepancies, determining if discrepancies correspond to polymorphisms and clone finishing. Designed to manage thousands of clones simultaneously, ACE maintains a relational database to store information about clones at various completion stages, project processing parameters and acceptance criteria. In a direct comparison, the automated analysis by ACE took less time and was more accurate than a manual analysis of a 93 gene clone set. Conclusion ACE was designed to facilitate high throughput clone sequence

  15. Clinical Chemistry Laboratory Automation in the 21st Century - Amat Victoria curam (Victory loves careful preparation)

    Science.gov (United States)

    Armbruster, David A; Overcash, David R; Reyes, Jaime

    2014-01-01

    The era of automation arrived with the introduction of the AutoAnalyzer using continuous flow analysis and the Robot Chemist that automated the traditional manual analytical steps. Successive generations of stand-alone analysers increased analytical speed, offered the ability to test high volumes of patient specimens, and provided large assay menus. A dichotomy developed, with a group of analysers devoted to performing routine clinical chemistry tests and another group dedicated to performing immunoassays using a variety of methodologies. Development of integrated systems greatly improved the analytical phase of clinical laboratory testing and further automation was developed for pre-analytical procedures, such as sample identification, sorting, and centrifugation, and post-analytical procedures, such as specimen storage and archiving. All phases of testing were ultimately combined in total laboratory automation (TLA) through which all modules involved are physically linked by some kind of track system, moving samples through the process from beginning-to-end. A newer and very powerful, analytical methodology is liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS). LC-MS/MS has been automated but a future automation challenge will be to incorporate LC-MS/MS into TLA configurations. Another important facet of automation is informatics, including middleware, which interfaces the analyser software to a laboratory information systems (LIS) and/or hospital information systems (HIS). This software includes control of the overall operation of a TLA configuration and combines analytical results with patient demographic information to provide additional clinically useful information. This review describes automation relevant to clinical chemistry, but it must be recognised that automation applies to other specialties in the laboratory, e.g. haematology, urinalysis, microbiology. It is a given that automation will continue to evolve in the clinical laboratory

  16. Automated patient and medication payment method for clinical trials

    Directory of Open Access Journals (Sweden)

    Yawn BP

    2013-01-01

    Full Text Available Barbara P Yawn,1 Suzanne Madison,1 Susan Bertram,1 Wilson D Pace,2 Anne Fuhlbrigge,3 Elliot Israel,3 Dawn Littlefield,1 Margary Kurland,1 Michael E Wechsler41Olmsted Medical Center, Department of Research, Rochester, MN, 2UCDHSC, Department of Family Medicine, University of Colorado Health Science Centre, Aurora, CO, 3Brigham and Women's Hospital, Pulmonary and Critical Care Division, Boston, MA, 4National Jewish Medical Center, Division of Pulmonology, Denver, CO, USABackground: Published reports and studies related to patient compensation for clinical trials focus primarily on the ethical issues related to appropriate amounts to reimburse for patient's time and risk burden. Little has been published regarding the method of payment for patient participation. As clinical trials move into widely dispersed community practices and more complex designs, the method of payment also becomes more complex. Here we review the decision process and payment method selected for a primary care-based randomized clinical trial of asthma management in Black Americans.Methods: The method selected is a credit card system designed specifically for clinical trials that allows both fixed and variable real-time payments. We operationalized the study design by providing each patient with two cards, one for reimbursement for study visits and one for payment of medication costs directly to the pharmacies.Results: Of the 1015 patients enrolled, only two refused use of the ClinCard, requesting cash payments for visits and only rarely a weekend or fill-in pharmacist refused to use the card system for payment directly to the pharmacy. Overall, the system has been well accepted by patients and local study teams. The ClinCard administrative system facilitates the fiscal accounting and medication adherence record-keeping by the central teams. Monthly fees are modest, and all 12 study institutional review boards approved use of the system without concern for patient

  17. Syncope: risk stratification and clinical decision making.

    Science.gov (United States)

    Peeters, Suzanne Y G; Hoek, Amber E; Mollink, Susan M; Huff, J Stephen

    2014-04-01

    Syncope is a common occurrence in the emergency department, accounting for approximately 1% to 3% of presentations. Syncope is best defined as a brief loss of consciousness and postural tone followed by spontaneous and complete recovery. The spectrum of etiologies ranges from benign to life threatening, and a structured approach to evaluating these patients is key to providing care that is thorough, yet cost-effective. This issue reviews the most relevant evidence for managing and risk stratifying the syncope patient, beginning with a focused history, physical examination, electrocardiogram, and tailored diagnostic testing. Several risk stratification decision rules are compared for performance in various scenarios, including how age and associated comorbidities may predict short-term and long-term adverse events. An algorithm for structured, evidence-based care of the syncope patient is included to ensure that patients requiring hospitalization are managed appropriately and those with benign causes are discharged safely.

  18. Toward Fully Automated Multicriterial Plan Generation: A Prospective Clinical Study

    International Nuclear Information System (INIS)

    Voet, Peter W.J.; Dirkx, Maarten L.P.; Breedveld, Sebastiaan; Fransen, Dennie; Levendag, Peter C.; Heijmen, Ben J.M.

    2013-01-01

    Purpose: To prospectively compare plans generated with iCycle, an in-house-developed algorithm for fully automated multicriterial intensity modulated radiation therapy (IMRT) beam profile and beam orientation optimization, with plans manually generated by dosimetrists using the clinical treatment planning system. Methods and Materials: For 20 randomly selected head-and-neck cancer patients with various tumor locations (of whom 13 received sequential boost treatments), we offered the treating physician the choice between an automatically generated iCycle plan and a manually optimized plan using standard clinical procedures. Although iCycle used a fixed “wish list” with hard constraints and prioritized objectives, the dosimetrists manually selected the beam configuration and fine tuned the constraints and objectives for each IMRT plan. Dosimetrists were not informed in advance whether a competing iCycle plan was made. The 2 plans were simultaneously presented to the physician, who then selected the plan to be used for treatment. For the patient group, differences in planning target volume coverage and sparing of critical tissues were quantified. Results: In 32 of 33 plan comparisons, the physician selected the iCycle plan for treatment. This highly consistent preference for the automatically generated plans was mainly caused by the improved sparing for the large majority of critical structures. With iCycle, the normal tissue complication probabilities for the parotid and submandibular glands were reduced by 2.4% ± 4.9% (maximum, 18.5%, P=.001) and 6.5% ± 8.3% (maximum, 27%, P=.005), respectively. The reduction in the mean oral cavity dose was 2.8 ± 2.8 Gy (maximum, 8.1 Gy, P=.005). For the swallowing muscles, the esophagus and larynx, the mean dose reduction was 3.3 ± 1.1 Gy (maximum, 9.2 Gy, P<.001). For 15 of the 20 patients, target coverage was also improved. Conclusions: In 97% of cases, automatically generated plans were selected for treatment because of

  19. Clinical decision support in community pharmacy

    NARCIS (Netherlands)

    Heringa, M.|info:eu-repo/dai/nl/412650207

    2017-01-01

    The occurrence of preventable patient harm caused by drug use has been shown over and over again. Clinical risk management is a concept to prevent patient harm by risk-reducing strategies. It is a systematic approach including risk detection, assessment, management and evaluation. One of the

  20. Cognitive Elements in Clinical Decision-Making

    Science.gov (United States)

    Dunphy, Bruce C.; Cantwell, Robert; Bourke, Sid; Fleming, Mark; Smith, Bruce; Joseph, K. S.; Dunphy, Stacey L

    2010-01-01

    Physician cognition, metacognition and affect may have an impact upon the quality of clinical reasoning. The purpose of this study was to examine the relationship between measures of physician metacognition and affect and patient outcomes in obstetric practice. Reflective coping (RC), proactive coping, need for cognition (NFC), tolerance for…

  1. Decision Analysis for Metric Selection on a Clinical Quality Scorecard.

    Science.gov (United States)

    Guth, Rebecca M; Storey, Patricia E; Vitale, Michael; Markan-Aurora, Sumita; Gordon, Randolph; Prevost, Traci Q; Dunagan, Wm Claiborne; Woeltje, Keith F

    2016-09-01

    Clinical quality scorecards are used by health care institutions to monitor clinical performance and drive quality improvement. Because of the rapid proliferation of quality metrics in health care, BJC HealthCare found it increasingly difficult to select the most impactful scorecard metrics while still monitoring metrics for regulatory purposes. A 7-step measure selection process was implemented incorporating Kepner-Tregoe Decision Analysis, which is a systematic process that considers key criteria that must be satisfied in order to make the best decision. The decision analysis process evaluates what metrics will most appropriately fulfill these criteria, as well as identifies potential risks associated with a particular metric in order to identify threats to its implementation. Using this process, a list of 750 potential metrics was narrowed to 25 that were selected for scorecard inclusion. This decision analysis process created a more transparent, reproducible approach for selecting quality metrics for clinical quality scorecards. © The Author(s) 2015.

  2. Comparison of manual and automated size measurements of lung metastases on MDCT images: Potential influence on therapeutic decisions

    Energy Technology Data Exchange (ETDEWEB)

    Pauls, Sandra [Department of Diagnostic and Interventional Radiology, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: sandra.pauls@uni-ulm.de; Kuerschner, Christian [Department of Diagnostic and Interventional Radiology, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: chris.kuerschner@web.de; Dharaiya, Ekta [CT-Clinical Science, Philips Medical Systems, Highland Heights, OH 44143 (United States)], E-mail: ekta.shah@philips.com; Muche, Rainer [Institute of Biometrics, University of Ulm, Schwabstrasse 13, 89075 Ulm (Germany)], E-mail: rainer.muche@uni-ulm.de; Schmidt, Stefan A. [Department of Diagnostic and Interventional Radiology, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: stefan-a.schmidt@gmx.de; Krueger, Stefan [Department of Internal Medicine II, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: s.krueger@uniklinik-ulm.de; Brambs, Hans-Juergen [Department of Diagnostic and Interventional Radiology, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: hans-juergen.brambs@uniklinik-ulm.de; Aschoff, Andrik J. [Department of Diagnostic and Interventional Radiology, University of Ulm, Robert-Koch-Strasse 8, 89081 Ulm (Germany)], E-mail: andrik.aschoff@uni-ulm.de

    2008-04-15

    Purpose: The goal of this study was to evaluate the influence of automated measurement of diameter, area, and volume from chest CT scans on therapeutic decisions of lung nodules as compared to manual 2-D measurements. Patients and method: The retrospective study involved 25 patients with 75 lung metastases. Contrast enhanced CT scans (16 row) of the lung were performed three times during chemotherapy with a mean time interval of 67.9 days between scans. In each patient, three metastases were evaluated (n = 225). Automatic measurements were compared to manual assessment for the following parameters: diameter, area, and density. The influence on the therapeutic decisions was evaluated using the RECIST criteria. Results: The maximum diameter measured by the automatic application was on an average 27% (S.D. 39; CI: 0.22-0.32; p < 0.0001) higher than the maximum diameter with manual assessment, and the differences depended on metastases size. Based on diameter calculation, manual and automated assessment disagreed in up to 32% of therapeutic decisions. Volumetric assessment tended towards more changes in therapy as compared to diameter calculation. The calculation of mean transversal area of metastases was 36% (S.D. 0.305; CI: -0.40 to -0.32; p < 0.0001) less with automated measurement. Therapeutic strategy would be changed in up to 25.7% of nodules using automated area calculation. Automated assessment of nodules' area and volume could influence the therapeutic decisions in up to 51.4% of all nodules. Density of the nodules was not validated to determine the influence on therapeutic decisions. Conclusion: There is a discrepancy between the manual and automated size measurement of lung metastases which could be significant.

  3. Comparison of manual and automated size measurements of lung metastases on MDCT images: Potential influence on therapeutic decisions

    International Nuclear Information System (INIS)

    Pauls, Sandra; Kuerschner, Christian; Dharaiya, Ekta; Muche, Rainer; Schmidt, Stefan A.; Krueger, Stefan; Brambs, Hans-Juergen; Aschoff, Andrik J.

    2008-01-01

    Purpose: The goal of this study was to evaluate the influence of automated measurement of diameter, area, and volume from chest CT scans on therapeutic decisions of lung nodules as compared to manual 2-D measurements. Patients and method: The retrospective study involved 25 patients with 75 lung metastases. Contrast enhanced CT scans (16 row) of the lung were performed three times during chemotherapy with a mean time interval of 67.9 days between scans. In each patient, three metastases were evaluated (n = 225). Automatic measurements were compared to manual assessment for the following parameters: diameter, area, and density. The influence on the therapeutic decisions was evaluated using the RECIST criteria. Results: The maximum diameter measured by the automatic application was on an average 27% (S.D. 39; CI: 0.22-0.32; p < 0.0001) higher than the maximum diameter with manual assessment, and the differences depended on metastases size. Based on diameter calculation, manual and automated assessment disagreed in up to 32% of therapeutic decisions. Volumetric assessment tended towards more changes in therapy as compared to diameter calculation. The calculation of mean transversal area of metastases was 36% (S.D. 0.305; CI: -0.40 to -0.32; p < 0.0001) less with automated measurement. Therapeutic strategy would be changed in up to 25.7% of nodules using automated area calculation. Automated assessment of nodules' area and volume could influence the therapeutic decisions in up to 51.4% of all nodules. Density of the nodules was not validated to determine the influence on therapeutic decisions. Conclusion: There is a discrepancy between the manual and automated size measurement of lung metastases which could be significant

  4. Clinical evaluation of automated processing of electrocardiograms by the Veterans Administration program (AVA 3.4).

    Science.gov (United States)

    Brohet, C R; Richman, H G

    1979-06-01

    Automated processing of electrocardiograms by the Veterans Administration program was evaluated for both agreement with physician interpretation and interpretative accuracy as assessed with nonelectrocardiographic criteria. One thousand unselected electrocardiograms were analyzed by two reviewer groups, one familiar and the other unfamiliar with the computer program. A significant number of measurement errors involving repolarization changes and left axis deviation occurred; however, interpretative disagreements related to statistical decision were largely language-related. Use of a printout with a more traditional format resulted in agreement with physician interpretation by both reviewer groups in more than 80 percent of cases. Overall sensitivity based on agreement with nonelectrocardiographic criteria was significantly greater with use of the computer program than with use of the conventional criteria utilized by the reviewers. This difference was particularly evident in the subgroup analysis of myocardial infarction and left ventricular hypertrophy. The degree of overdiagnosis of left ventricular hypertrophy and posteroinferior infarction was initially unacceptable, but this difficulty was corrected by adjustment of probabilities. Clinical acceptability of the Veterans Administration program appears to require greater physician education than that needed for other computer programs of electrocardiographic analysis; the flexibility of interpretation by statistical decision offers the potential for better diagnostic accuracy.

  5. A Solution Generator Algorithm for Decision Making based Automated Negotiation in the Construction Domain

    Directory of Open Access Journals (Sweden)

    Arazi Idrus

    2017-12-01

    Full Text Available In this paper, we present our work-in-progress of a proposed framework for automated negotiation in the construction domain. The proposed framework enables software agents to conduct negotiations and autonomously make value-based decisions. The framework consists of three main components which are, solution generator algorithm, negotiation algorithm, and conflict resolution algorithm. This paper extends the discussion on the solution generator algorithm that enables software agents to generate solutions and rank them from 1st to nth solution for the negotiation stage of the operation. The solution generator algorithm consists of three steps which are, review solutions, rank solutions, and form ranked solutions. For validation purpose, we present a scenario that utilizes the proposed algorithm to rank solutions. The validation shows that the algorithm is promising, however, it also highlights the conflict between different parties that needs further negotiation action.

  6. Grand Challenges in Clinical Decision Support v10

    Science.gov (United States)

    Sittig, Dean F.; Wright, Adam; Osheroff, Jerome A.; Middleton, Blackford; Teich, Jonathan M.; Ash, Joan S.; Campbell, Emily; Bates, David W.

    2008-01-01

    There is a pressing need for high-quality, effective means of designing, developing, presenting, implementing, evaluating, and maintaining all types of clinical decision support capabilities for clinicians, patients and consumers. Using an iterative, consensus-building process we identified a rank-ordered list of the top 10 grand challenges in clinical decision support. This list was created to educate and inspire researchers, developers, funders, and policy-makers. The list of challenges in order of importance that they be solved if patients and organizations are to begin realizing the fullest benefits possible of these systems consists of: Improve the human-computer interface; Disseminate best practices in CDS design, development, and implementation; Summarize patient-level information; Prioritize and filter recommendations to the user; Create an architecture for sharing executable CDS modules and services; Combine recommendations for patients with co-morbidities; Prioritize CDS content development and implementation; Create internet-accessible clinical decision support repositories; Use freetext information to drive clinical decision support; Mine large clinical databases to create new CDS. Identification of solutions to these challenges is critical if clinical decision support is to achieve its potential and improve the quality, safety and efficiency of healthcare. PMID:18029232

  7. The impact of an electronic clinical decision support for pulmonary ...

    African Journals Online (AJOL)

    State-of-the-art electronic radiology workflow can provide clinical decision support (CDS) for specialised imaging requests, but there has been limited work on the clinical impact of CDS in PE, particularly in resource-constrained environments. Objective. To determine the impact of an electronic CDS for PE on the efficiency ...

  8. Cholgate - a randomized controlled trial comparing the effect of automated and on-demand decision support on the management of cardiovascular disease factors in primary care

    NARCIS (Netherlands)

    J.T. van Wyk (Jacobus); M.A.M. van Wijk (Marc); P.W. Moorman (Peter); M. Mosseveld (Mees); J. van der Lei (Johan)

    2003-01-01

    textabstractAutomated and on-demand decision support systems integrated into an electronic medical record have proven to be an effective implementation strategy for guidelines. Cholgate is a randomized controlled trial comparing the effect of automated and on-demand decision

  9. Quantitative Analysis of Uncertainty in Medical Reporting: Part 3: Customizable Education, Decision Support, and Automated Alerts.

    Science.gov (United States)

    Reiner, Bruce I

    2017-12-18

    In order to better elucidate and understand the causative factors and clinical implications of uncertainty in medical reporting, one must first create a referenceable database which records a number of standardized metrics related to uncertainty language, clinical context, technology, and provider and patient data. The resulting analytics can in turn be used to create context and user-specific reporting guidelines, real-time decision support, educational resources, and quality assurance measures. If this technology can be directly integrated into reporting technology and workflow, the goal is to proactively improve clinical outcomes at the point of care.

  10. Datafication of Automated (Legal) Decisions - or how (not) to install a GPS when law is not precisely a map

    DEFF Research Database (Denmark)

    Schaumburg-Müller, Sten

    situations to closed situations with a vast, but technically manageable amount of fixed data – driving cars may be a good example – it may be counterproductive to reduce all situations to categorizationable and foreseeable ones. This automation skepticism hinges on various concepts such as ‘tychism’ (Peirce......Even though I maintain that it is a misconception to state that states are “no longer” the only actors, since they never were, indeed it makes sense to “shed light on the impact of (…) new tendencies on legal regulatory mechanisms (…)” One regulatory tendency is obviously the automation of (legal......) decisions which has implications for legal orders, legal actors and legal research, not to mention legal legitimacy as well as personal autonomy and democracy. On the one hand automation may facilitate better, faster, more predictable and more coherent decisions and leave cumbersome and time consuming...

  11. Clinical decision-making by midwives: managing case complexity.

    Science.gov (United States)

    Cioffi, J; Markham, R

    1997-02-01

    In making clinical judgements, it is argued that midwives use 'shortcuts' or heuristics based on estimated probabilities to simplify the decision-making task. Midwives (n = 30) were given simulated patient assessment situations of high and low complexity and were required to think aloud. Analysis of verbal protocols showed that subjective probability judgements (heuristics) were used more frequently in the high than low complexity case and predominated in the last quarter of the assessment period for the high complexity case. 'Representativeness' was identified more frequently in the high than in the low case, but was the dominant heuristic in both. Reports completed after each simulation suggest that heuristics based on memory for particular conditions affect decisions. It is concluded that midwives use heuristics, derived mainly from their clinical experiences, in an attempt to save cognitive effort and to facilitate reasonably accurate decisions in the decision-making process.

  12. Decision-theoretic planning of clinical patient management

    OpenAIRE

    Peek, Niels Bastiaan

    2000-01-01

    When a doctor is treating a patient, he is constantly facing decisions. From the externally visible signs and symptoms he must establish a hypothesis of what might be wrong with the patient; then he must decide whether additional diagnostic procedures are required to verify this hypothesis, whether therapeutic action is necessary, and which post-therapeutic trajectory is to be followed. All these bedside decisions are related to each other, and the whole task of clinical patient management ca...

  13. The thinking doctor: clinical decision making in contemporary medicine.

    Science.gov (United States)

    Trimble, Michael; Hamilton, Paul

    2016-08-01

    Diagnostic errors are responsible for a significant number of adverse events. Logical reasoning and good decision-making skills are key factors in reducing such errors, but little emphasis has traditionally been placed on how these thought processes occur, and how errors could be minimised. In this article, we explore key cognitive ideas that underpin clinical decision making and suggest that by employing some simple strategies, physicians might be better able to understand how they make decisions and how the process might be optimised. © 2016 Royal College of Physicians.

  14. Improving clinical decision support using data mining techniques

    Science.gov (United States)

    Burn-Thornton, Kath E.; Thorpe, Simon I.

    1999-02-01

    Physicians, in their ever-demanding jobs, are looking to decision support systems for aid in clinical diagnosis. However, clinical decision support systems need to be of sufficiently high accuracy that they help, rather than hinder, the physician in his/her diagnosis. Decision support systems with accuracies, of patient state determination, of greater than 80 percent, are generally perceived to be sufficiently accurate to fulfill the role of helping the physician. We have previously shown that data mining techniques have the potential to provide the underpinning technology for clinical decision support systems. In this paper, an extension of the work in reverence 2, we describe how changes in data mining methodologies, for the analysis of 12-lead ECG data, improve the accuracy by which data mining algorithms determine which patients are suffering from heart disease. We show that the accuracy of patient state prediction, for all the algorithms, which we investigated, can be increased by up to 6 percent, using the combination of appropriate test training ratios and 5-fold cross-validation. The use of cross-validation greater than 5-fold, appears to reduce the improvement in algorithm classification accuracy gained by the use of this validation method. The accuracy of 84 percent in patient state predictions, obtained using the algorithm OCI, suggests that this algorithm will be capable of providing the required accuracy for clinical decision support systems.

  15. Nomenclature and basic concepts in automation in the clinical laboratory setting: a practical glossary.

    Science.gov (United States)

    Evangelopoulos, Angelos A; Dalamaga, Maria; Panoutsopoulos, Konstantinos; Dima, Kleanthi

    2013-01-01

    In the early 80s, the word automation was used in the clinical laboratory setting referring only to analyzers. But in late 80s and afterwards, automation found its way into all aspects of the diagnostic process, embracing not only the analytical but also the pre- and post-analytical phase. While laboratories in the eastern world, mainly Japan, paved the way for laboratory automation, US and European laboratories soon realized the benefits and were quick to follow. Clearly, automation and robotics will be a key survival tool in a very competitive and cost-concious healthcare market. What sets automation technology apart from so many other efficiency solutions are the dramatic savings that it brings to the clinical laboratory. Further standardization will assure the success of this revolutionary new technology. One of the main difficulties laboratory managers and personnel must deal with when studying solutions to reengineer a laboratory is familiarizing themselves with the multidisciplinary and technical terminology of this new and exciting field. The present review/glossary aims at giving an overview of the most frequently used terms within the scope of laboratory automation and to put laboratory automation on a sounder linguistic basis.

  16. The role of emotions in clinical reasoning and decision making.

    Science.gov (United States)

    Marcum, James A

    2013-10-01

    What role, if any, should emotions play in clinical reasoning and decision making? Traditionally, emotions have been excluded from clinical reasoning and decision making, but with recent advances in cognitive neuropsychology they are now considered an important component of them. Today, cognition is thought to be a set of complex processes relying on multiple types of intelligences. The role of mathematical logic (hypothetico-deductive thinking) or verbal linguistic intelligence in cognition, for example, is well documented and accepted; however, the role of emotional intelligence has received less attention-especially because its nature and function are not well understood. In this paper, I argue for the inclusion of emotions in clinical reasoning and decision making. To that end, developments in contemporary cognitive neuropsychology are initially examined and analyzed, followed by a review of the medical literature discussing the role of emotions in clinical practice. Next, a published clinical case is reconstructed and used to illustrate the recognition and regulation of emotions played during a series of clinical consultations, which resulted in a positive medical outcome. The paper's main thesis is that emotions, particularly in terms of emotional intelligence as a practical form of intelligence, afford clinical practitioners a robust cognitive resource for providing quality medical care.

  17. A systematic literature review of automated clinical coding and classification systems.

    Science.gov (United States)

    Stanfill, Mary H; Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

    2010-01-01

    Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.

  18. The Utility of the Frailty Index in Clinical Decision Making.

    Science.gov (United States)

    Khatry, K; Peel, N M; Gray, L C; Hubbard, R E

    2018-01-01

    Using clinical vignettes, this study aimed to determine if a measure of patient frailty would impact management decisions made by geriatricians regarding commonly encountered clinical situations. Electronic surveys consisting of three vignettes derived from cases commonly seen in an acute inpatient ward were distributed to geriatricians. Vignettes included patients being considered for intensive care treatment, rehabilitation, or coronary artery bypass surgery. A frailty index was generated through Comprehensive electronic Geriatric Assessment. For each vignette, respondents were asked to make a recommendation for management, based on either a brief or detailed amount of clinical information and to reconsider their decision after the addition of the frailty index. The study suggests that quantification of frailty might aid the clinical judgment now employed daily to proceed with usual care, or to modify it based on the vulnerability of the person to whom it is aimed.

  19. Risk perception and clinical decision making in primary care

    DEFF Research Database (Denmark)

    Barfoed, Benedicte Marie Lind

    2015-01-01

    Objectives We aim to present new knowledge about different perspectives of health care professionals’ risk perceptions and clinical decision making. Furthermore, we intend to discuss differences between professional and personal risk perceptions and the impact on decisions in terms of both short...... and long-term outcomes. Background Insight into healthcare professionals’ perception of risk is a cornerstone for understanding their strategies for practising preventive care. The way people perceive risk can be seen as part of a general personality trait influenced by a mixture of individual...... considerations and the specific context. Most research has been focused on understanding of the concepts of risk. However healthcare professionals’ risk perception and personal attitudes also affect their clinical decision-making and risk communication. The differences between health care professionals’ personal...

  20. The relationship between patient data and pooled clinical management decisions.

    Science.gov (United States)

    Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

    2013-01-01

    A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient

  1. Using Clinical Decision Support Software in Health Insurance Company

    Science.gov (United States)

    Konovalov, R.; Kumlander, Deniss

    This paper proposes the idea to use Clinical Decision Support software in Health Insurance Company as a tool to reduce the expenses related to Medication Errors. As a prove that this class of software will help insurance companies reducing the expenses, the research was conducted in eight hospitals in United Arab Emirates to analyze the amount of preventable common Medication Errors in drug prescription.

  2. Clinical decisions for anterior restorations: the concept of restorative volume.

    Science.gov (United States)

    Cardoso, Jorge André; Almeida, Paulo Júlio; Fischer, Alex; Phaxay, Somano Luang

    2012-12-01

    The choice of the most appropriate restoration for anterior teeth is often a difficult decision. Numerous clinical and technical factors play an important role in selecting the treatment option that best suits the patient and the restorative team. Experienced clinicians have developed decision processes that are often more complex than may seem. Less experienced professionals may find difficulties making treatment decisions because of the widely varied restorative materials available and often numerous similar products offered by different manufacturers. The authors reviewed available evidence and integrated their clinical experience to select relevant factors that could provide a logical and practical guideline for restorative decisions in anterior teeth. The presented concept of restorative volume is based on structural, optical, and periodontal factors. Each of these factors will influence the short- and long-term behavior of restorations in terms of esthetics, biology, and function. Despite the marked evolution of esthetic restorative techniques and materials, significant limitations still exist, which should be addressed by researchers. The presented guidelines must be regarded as a mere orientation for risk analysis. A comprehensive individual approach should always be the core of restorative esthetic treatments. The complex decision process for anterior esthetic restorations can be clarified by a systematized examination of structural, optical, and periodontal factors. The basis for the proposed thought process is the concept of restorative volume that is a contemporary interpretation of restoration categories and their application. © 2012 Wiley Periodicals, Inc.

  3. Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review

    Directory of Open Access Journals (Sweden)

    Wu Helen W

    2012-08-01

    Full Text Available Abstract Background Greater use of computerized decision support (DS systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS. Methods Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1 provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2 involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Results Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective; allowing for contingent adaptations; and facilitating

  4. Advancing clinical decision support using lessons from outside of healthcare: an interdisciplinary systematic review.

    Science.gov (United States)

    Wu, Helen W; Davis, Paul K; Bell, Douglas S

    2012-08-17

    Greater use of computerized decision support (DS) systems could address continuing safety and quality problems in healthcare, but the healthcare field has struggled to implement DS technology. This study surveys DS experience across multiple non-healthcare disciplines for new insights that are generalizable to healthcare provider decisions. In particular, it sought design principles and lessons learned from the other disciplines that could inform efforts to accelerate the adoption of clinical decision support (CDS). Our systematic review drew broadly from non-healthcare databases in the basic sciences, social sciences, humanities, engineering, business, and defense: PsychINFO, BusinessSource Premier, Social Sciences Abstracts, Web of Science, and Defense Technical Information Center. Because our interest was in DS that could apply to clinical decisions, we selected articles that (1) provided a review, overview, discussion of lessons learned, or an evaluation of design or implementation aspects of DS within a non-healthcare discipline and (2) involved an element of human judgment at the individual level, as opposed to decisions that can be fully automated or that are made at the organizational level. Clinical decisions share some similarities with decisions made by military commanders, business managers, and other leaders: they involve assessing new situations and choosing courses of action with major consequences, under time pressure, and with incomplete information. We identified seven high-level DS system design features from the non-healthcare literature that could be applied to CDS: providing broad, system-level perspectives; customizing interfaces to specific users and roles; making the DS reasoning transparent; presenting data effectively; generating multiple scenarios covering disparate outcomes (e.g., effective; effective with side effects; ineffective); allowing for contingent adaptations; and facilitating collaboration. The article provides examples of

  5. Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability.

    Science.gov (United States)

    Kinnear, John; Jackson, Ruth

    2017-07-01

    Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, pprobability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  6. Continuous quality improvement for the clinical decision unit.

    Science.gov (United States)

    Mace, Sharon E

    2004-01-01

    Clinical decision units (CDUs) are a relatively new and growing area of medicine in which patients undergo rapid evaluation and treatment. Continuous quality improvement (CQI) is important for the establishment and functioning of CDUs. CQI in CDUs has many advantages: better CDU functioning, fulfillment of Joint Commission on Accreditation of Healthcare Organizations mandates, greater efficiency/productivity, increased job satisfaction, better performance improvement, data availability, and benchmarking. Key elements include a database with volume indicators, operational policies, clinical practice protocols (diagnosis specific/condition specific), monitors, benchmarks, and clinical pathways. Examples of these important parameters are given. The CQI process should be individualized for each CDU and hospital.

  7. Whole mind and shared mind in clinical decision-making.

    Science.gov (United States)

    Epstein, Ronald Mark

    2013-02-01

    To review the theory, research evidence and ethical implications regarding "whole mind" and "shared mind" in clinical practice in the context of chronic and serious illnesses. Selective critical review of the intersection of classical and naturalistic decision-making theories, cognitive neuroscience, communication research and ethics as they apply to decision-making and autonomy. Decision-making involves analytic thinking as well as affect and intuition ("whole mind") and sharing cognitive and affective schemas of two or more individuals ("shared mind"). Social relationships can help processing of complex information that otherwise would overwhelm individuals' cognitive capacities. Medical decision-making research, teaching and practice should consider both analytic and non-analytic cognitive processes. Further, research should consider that decisions emerge not only from the individual perspectives of patients, their families and clinicians, but also the perspectives that emerge from the interactions among them. Social interactions have the potential to enhance individual autonomy, as well as to promote relational autonomy based on shared frames of reference. Shared mind has the potential to result in wiser decisions, greater autonomy and self-determination; yet, clinicians and patients should be vigilant for the potential of hierarchical relationships to foster coercion or silencing of the patient's voice. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  8. Complex contexts and relationships affect clinical decisions in group therapy.

    Science.gov (United States)

    Tasca, Giorgio A; Mcquaid, Nancy; Balfour, Louise

    2016-09-01

    Clinical errors tend to be underreported even though examining them can provide important training and professional development opportunities. The group therapy context may be prone to clinician errors because of the added complexity within which therapists work and patients receive treatment. We discuss clinical errors that occurred within a group therapy in which a patient for whom group was not appropriate was admitted to the treatment and then was not removed by the clinicians. This was countertherapeutic for both patient and group. Two clinicians were involved: a clinical supervisor who initially assessed and admitted the patient to the group, and a group therapist. To complicate matters, the group therapy occurred within the context of a clinical research trial. The errors, possible solutions, and recommendations are discussed within Reason's Organizational Accident Model (Reason, 2000). In particular, we discuss clinician errors in the context of countertransference and clinician heuristics, group therapy as a local work condition that complicates clinical decision-making, and the impact of the research context as a latent organizational factor. We also present clinical vignettes from the pregroup preparation, group therapy, and supervision. Group therapists are more likely to avoid errors in clinical decisions if they engage in reflective practice about their internal experiences and about the impact of the context in which they work. Therapists must keep in mind the various levels of group functioning, especially related to the group-as-a-whole (i.e., group composition, cohesion, group climate, and safety) when making complex clinical decisions in order to optimize patient outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  9. System of automated processing of radionuclide investigations (SAPRI-01) in clinical practice

    International Nuclear Information System (INIS)

    Sivachenko, T.P.; Mechev, D.S.; Krupka, I.N.

    1988-01-01

    The author described the results of clinical testing of a system SAPRI-01 designed for automated collection, storage and processing of data on radionuclide investigations. He gave examples of automated processing of RCG and the results of positive scintigraphy of tumors of different sites using 67 Ga-citrate and 99m Tc pertechnetate in statistical and dynamic investigations. Short-comings and ways for updating 4 the system during its serial production were pointed out. The introduction of the system into clinical practice on a wide scale was shown to hold promise

  10. Decision-table development for use with the CAT code for the automated fault-tree construction

    International Nuclear Information System (INIS)

    Wu, J.S.; Salem, S.L.; Apostolakis, G.E.

    1977-01-01

    A library of decision tables to be used in connection with the CAT computer code for the automated construction of fault trees is presented. A decision table is constructed for each component type describing the output of the component in terms of its inputs and its internal states. In addition, a modification of the CAT code that couples it with a fault tree analysis code is presented. This report represents one aspect of a study entitled, 'A General Evaluation Approach to Risk-Benefit for Large Technological Systems, and Its Application to Nuclear Power.'

  11. Future of Earthquake Early Warning: Quantifying Uncertainty and Making Fast Automated Decisions for Applications

    Science.gov (United States)

    Wu, Stephen

    Earthquake early warning (EEW) systems have been rapidly developing over the past decade. Japan Meteorological Agency (JMA) has an EEW system that was operating during the 2011 M9 Tohoku earthquake in Japan, and this increased the awareness of EEW systems around the world. While longer-time earthquake prediction still faces many challenges to be practical, the availability of shorter-time EEW opens up a new door for earthquake loss mitigation. After an earthquake fault begins rupturing, an EEW system utilizes the first few seconds of recorded seismic waveform data to quickly predict the hypocenter location, magnitude, origin time and the expected shaking intensity level around the region. This early warning information is broadcast to different sites before the strong shaking arrives. The warning lead time of such a system is short, typically a few seconds to a minute or so, and the information is uncertain. These factors limit human intervention to activate mitigation actions and this must be addressed for engineering applications of EEW. This study applies a Bayesian probabilistic approach along with machine learning techniques and decision theories from economics to improve different aspects of EEW operation, including extending it to engineering applications. Existing EEW systems are often based on a deterministic approach. Often, they assume that only a single event occurs within a short period of time, which led to many false alarms after the Tohoku earthquake in Japan. This study develops a probability-based EEW algorithm based on an existing deterministic model to extend the EEW system to the case of concurrent events, which are often observed during the aftershock sequence after a large earthquake. To overcome the challenge of uncertain information and short lead time of EEW, this study also develops an earthquake probability-based automated decision-making (ePAD) framework to make robust decision for EEW mitigation applications. A cost-benefit model that

  12. Towards Automation 2.0: A Neurocognitive Model for Environment Recognition, Decision-Making, and Action Execution

    Directory of Open Access Journals (Sweden)

    Zucker Gerhard

    2011-01-01

    Full Text Available The ongoing penetration of building automation by information technology is by far not saturated. Today's systems need not only be reliable and fault tolerant, they also have to regard energy efficiency and flexibility in the overall consumption. Meeting the quality and comfort goals in building automation while at the same time optimizing towards energy, carbon footprint and cost-efficiency requires systems that are able to handle large amounts of information and negotiate system behaviour that resolves conflicting demands—a decision-making process. In the last years, research has started to focus on bionic principles for designing new concepts in this area. The information processing principles of the human mind have turned out to be of particular interest as the mind is capable of processing huge amounts of sensory data and taking adequate decisions for (re-actions based on these analysed data. In this paper, we discuss how a bionic approach can solve the upcoming problems of energy optimal systems. A recently developed model for environment recognition and decision-making processes, which is based on research findings from different disciplines of brain research is introduced. This model is the foundation for applications in intelligent building automation that have to deal with information from home and office environments. All of these applications have in common that they consist of a combination of communicating nodes and have many, partly contradicting goals.

  13. Real-Time Clinical Decision Support Decreases Inappropriate Plasma Transfusion.

    Science.gov (United States)

    Shah, Neil; Baker, Steven A; Spain, David; Shieh, Lisa; Shepard, John; Hadhazy, Eric; Maggio, Paul; Goodnough, Lawrence T

    2017-08-01

    To curtail inappropriate plasma transfusions, we instituted clinical decision support as an alert upon order entry if the patient's recent international normalized ratio (INR) was 1.7 or less. The alert was suppressed for massive transfusion and within operative or apheresis settings. The plasma order was automatically removed upon alert acceptance while clinical exception reasons allowed for continued transfusion. Alert impact was studied comparing a 7-month control period with a 4-month intervention period. Monthly plasma utilization decreased 17.4%, from a mean ± SD of 3.40 ± 0.48 to 2.82 ± 0.6 plasma units per hundred patient days (95% confidence interval [CI] of difference, -0.1 to 1.3). Plasma transfused below an INR of 1.7 or less decreased from 47.6% to 41.6% (P = .0002; odds ratio, 0.78; 95% CI, 0.69-0.89). The alert recommendation was accepted 33% of the time while clinical exceptions were chosen in the remaining cases (active bleeding, 31%; other clinical indication, 33%; and apheresis, 2%). Alert acceptance rate varied significantly among different provider specialties. Clinical decision support can help curtail inappropriate plasma use but needs to be part of a comprehensive strategy including audit and feedback for comprehensive, long-term changes. © American Society for Clinical Pathology, 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  14. An Automated Approach for Ranking Journals to Help in Clinician Decision Support

    Science.gov (United States)

    Jonnalagadda, Siddhartha R.; Moosavinasab, Soheil; Nath, Chinmoy; Li, Dingcheng; Chute, Christopher G.; Liu, Hongfang

    2014-01-01

    Point of care access to knowledge from full text journal articles supports decision-making and decreases medical errors. However, it is an overwhelming task to search through full text journal articles and find quality information needed by clinicians. We developed a method to rate journals for a given clinical topic, Congestive Heart Failure (CHF). Our method enables filtering of journals and ranking of journal articles based on source journal in relation to CHF. We also obtained a journal priority score, which automatically rates any journal based on its importance to CHF. Comparing our ranking with data gathered by surveying 169 cardiologists, who publish on CHF, our best Multiple Linear Regression model showed a correlation of 0.880, based on five-fold cross validation. Our ranking system can be extended to other clinical topics. PMID:25954382

  15. Evaluating online diagnostic decision support tools for the clinical setting.

    Science.gov (United States)

    Pryor, Marie; White, David; Potter, Bronwyn; Traill, Roger

    2012-01-01

    Clinical decision support tools available at the point of care are an effective adjunct to support clinicians to make clinical decisions and improve patient outcomes. We developed a methodology and applied it to evaluate commercially available online clinical diagnostic decision support (DDS) tools for use at the point of care. We identified 11 commercially available DDS tools and assessed these against an evaluation instrument that included 6 categories; general information, content, quality control, search, clinical results and other features. We developed diagnostically challenging clinical case scenarios based on real patient experience that were commonly missed by junior medical staff. The evaluation was divided into 2 phases; an initial evaluation of all identified and accessible DDS tools conducted by the Clinical Information Access Portal (CIAP) team and a second phase that further assessed the top 3 tools identified in the initial evaluation phase. An evaluation panel consisting of senior and junior medical clinicians from NSW Health conducted the second phase. Of the eleven tools that were assessed against the evaluation instrument only 4 tools completely met the DDS definition that was adopted for this evaluation and were able to produce a differential diagnosis. From the initial phase of the evaluation 4 DDS tools scored 70% or more (maximum score 96%) for the content category, 8 tools scored 65% or more (maximum 100%) for the quality control category, 5 tools scored 65% or more (maximum 94%) for the search category, and 4 tools score 70% or more (maximum 81%) for the clinical results category. The second phase of the evaluation was focused on assessing diagnostic accuracy for the top 3 tools identified in the initial phase. Best Practice ranked highest overall against the 6 clinical case scenarios used. Overall the differentiating factor between the top 3 DDS tools was determined by diagnostic accuracy ranking, ease of use and the confidence and

  16. Clinical Decision Making of Nurses Working in Hospital Settings

    Directory of Open Access Journals (Sweden)

    Ida Torunn Bjørk

    2011-01-01

    Full Text Available This study analyzed nurses' perceptions of clinical decision making (CDM in their clinical practice and compared differences in decision making related to nurse demographic and contextual variables. A cross-sectional survey was carried out with 2095 nurses in four hospitals in Norway. A 24-item Nursing Decision Making Instrument based on cognitive continuum theory was used to explore how nurses perceived their CDM when meeting an elective patient for the first time. Data were analyzed with descriptive frequencies, t-tests, Chi-Square test, and linear regression. Nurses' decision making was categorized into analytic-systematic, intuitive-interpretive, and quasi-rational models of CDM. Most nurses reported the use of quasi-rational models during CDM thereby supporting the tenet that cognition most often includes properties of both analysis and intuition. Increased use of intuitive-interpretive models of CDM was associated with years in present job, further education, male gender, higher age, and working in predominantly surgical units.

  17. IBM’s Health Analytics and Clinical Decision Support

    Science.gov (United States)

    Sun, J.; Knoop, S.; Shabo, A.; Carmeli, B.; Sow, D.; Syed-Mahmood, T.; Rapp, W.

    2014-01-01

    Summary Objectives This survey explores the role of big data and health analytics developed by IBM in supporting the transformation of healthcare by augmenting evidence-based decision-making. Methods Some problems in healthcare and strategies for change are described. It is argued that change requires better decisions, which, in turn, require better use of the many kinds of healthcare information. Analytic resources that address each of the information challenges are described. Examples of the role of each of the resources are given. Results There are powerful analytic tools that utilize the various kinds of big data in healthcare to help clinicians make more personalized, evidenced-based decisions. Such resources can extract relevant information and provide insights that clinicians can use to make evidence-supported decisions. There are early suggestions that these resources have clinical value. As with all analytic tools, they are limited by the amount and quality of data. Conclusion Big data is an inevitable part of the future of healthcare. There is a compelling need to manage and use big data to make better decisions to support the transformation of healthcare to the personalized, evidence-supported model of the future. Cognitive computing resources are necessary to manage the challenges in employing big data in healthcare. Such tools have been and are being developed. The analytic resources, themselves, do not drive, but support healthcare transformation. PMID:25123736

  18. Experiential and rational decision making: a survey to determine how emergency physicians make clinical decisions.

    Science.gov (United States)

    Calder, Lisa A; Forster, Alan J; Stiell, Ian G; Carr, Laura K; Brehaut, Jamie C; Perry, Jeffrey J; Vaillancourt, Christian; Croskerry, Patrick

    2012-10-01

    Dual-process psychological theories argue that clinical decision making is achieved through a combination of experiential (fast and intuitive) and rational (slower and systematic) cognitive processes. To determine whether emergency physicians perceived their clinical decisions in general to be more experiential or rational and how this compared with other physicians. A validated psychometric tool, the Rational Experiential Inventory (REI-40), was sent through postal mail to all emergency physicians registered with the College of Physicians and Surgeons of Ontario, according to their website in November 2009. Forty statements were ranked on a Likert scale from 1 (Definitely False) to 5 (Definitely True). An initial survey was sent out, followed by reminder cards and a second survey to non-respondents. Analysis included descriptive statistics, Student t tests, analysis of variance and comparison of mean scores with those of cardiologists from New Zealand. The response rate in this study was 46.9% (434/925). The respondents' median age was 41-50 years; they were mostly men (72.6%) and most had more than 10 years of clinical experience (66.8%). The mean REI-40 rational scores were higher than the experiential scores (3.93/5 (SD 0.35) vs 3.33/5 (SD 0.49), prational 3.93/5, mean experiential 3.05/5). The mean experiential scores were significantly higher for female respondents than for male respondents (3.40/5 (SD 0.49) vs 3.30/5 (SD 0.48), p=0.003). Overall, emergency physicians favoured rational decision making rather than experiential decision making; however, female emergency physicians had higher experiential scores than male emergency physicians. This has important implications for future knowledge translation and decision support efforts among emergency physicians.

  19. Clinical decision-making of rural novice nurses.

    Science.gov (United States)

    Seright, T J

    2011-01-01

    Nurses in rural settings are often the first to assess and interpret the patient's clinical presentations. Therefore, an understanding of how nurses experience decision-making is important in terms of educational preparation, resource allocation to rural areas, institutional cultures, and patient outcomes. Theory development was based on the in-depth investigation of 12 novice nurses practicing in rural critical access hospitals in a north central state. This grounded theory study consisted of face-to-face interviews with 12 registered nurses, nine of whom were observed during their work day. The participants were interviewed a second time, as a method of member checking, and during this interview they reviewed their transcripts, the emerging themes and categories. Directors of nursing from both the research sites and rural hospitals not involved in the study, experienced researchers, and nurse educators facilitated triangulation of the findings. 'Sociocentric rationalizing' emerged as the central phenomenon and referred to the sense of belonging and agency which impacted the decision-making in this small group of novice nurses in rural critical access hospitals. The observed consequences, which were conceptualized during the axial coding process and were derived from observations and interviews of the 12 novice nurses in this study include: (1) gathering information before making a decision included assessment of: the credibility of co-workers, patients' subjective and objective data, and one's own past and current experiences; (2) conferring with co-workers as a direct method of confirming/denying decisions being made was considered more realistic and expedient than policy books and decision trees; (3) rural practicum clinical experiences, along with support after orientation, provide for transition to the rural nurse role; (4) involved directors of nursing served as both models and protectors of novice nurses placed in high accountability positions early in

  20. Clinical utility of an automated immunochemiluminometric thyroglobulin assay in differentiated thyroid carcinoma

    NARCIS (Netherlands)

    Persoon, ACM; Van den Ouweland, JMW; Wilde, J; Kema, IP; Wolffenbuttel, BHR; Links, TP

    Background: Thyroglobulin (Tg) measurements are important in the follow-up of patients with differentiated thyroid carcinoma (DTC). We evaluated the analytical and clinical performance of a new automated immunochemiluminometric assay for Tg (Tg-ICMA; Nichols Advantage Tg; Nichols Institute

  1. Challenges in clinical natural language processing for automated disorder normalization.

    Science.gov (United States)

    Leaman, Robert; Khare, Ritu; Lu, Zhiyong

    2015-10-01

    Identifying key variables such as disorders within the clinical narratives in electronic health records has wide-ranging applications within clinical practice and biomedical research. Previous research has demonstrated reduced performance of disorder named entity recognition (NER) and normalization (or grounding) in clinical narratives than in biomedical publications. In this work, we aim to identify the cause for this performance difference and introduce general solutions. We use closure properties to compare the richness of the vocabulary in clinical narrative text to biomedical publications. We approach both disorder NER and normalization using machine learning methodologies. Our NER methodology is based on linear-chain conditional random fields with a rich feature approach, and we introduce several improvements to enhance the lexical knowledge of the NER system. Our normalization method - never previously applied to clinical data - uses pairwise learning to rank to automatically learn term variation directly from the training data. We find that while the size of the overall vocabulary is similar between clinical narrative and biomedical publications, clinical narrative uses a richer terminology to describe disorders than publications. We apply our system, DNorm-C, to locate disorder mentions and in the clinical narratives from the recent ShARe/CLEF eHealth Task. For NER (strict span-only), our system achieves precision=0.797, recall=0.713, f-score=0.753. For the normalization task (strict span+concept) it achieves precision=0.712, recall=0.637, f-score=0.672. The improvements described in this article increase the NER f-score by 0.039 and the normalization f-score by 0.036. We also describe a high recall version of the NER, which increases the normalization recall to as high as 0.744, albeit with reduced precision. We perform an error analysis, demonstrating that NER errors outnumber normalization errors by more than 4-to-1. Abbreviations and acronyms are found

  2. Clinical utility of an automated instrument for gram staining single slides.

    Science.gov (United States)

    Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

    2010-06-01

    Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis.

  3. Clinical Utility of an Automated Instrument for Gram Staining Single Slides ▿

    Science.gov (United States)

    Baron, Ellen Jo; Mix, Samantha; Moradi, Wais

    2010-01-01

    Gram stains of 87 different clinical samples were prepared by the laboratory's conventional methods (automated or manual) and by a new single-slide-type automated staining instrument, GG&B AGS-1000. Gram stains from either heat- or methanol-fixed slides stained with the new instrument were easy to interpret, and results were essentially the same as those from the methanol-fixed slides prepared as a part of the routine workflow. This instrument is well suited to a rapid-response laboratory where Gram stain requests are commonly received on a stat basis. PMID:20410348

  4. Automated interpretable computational biology in the clinic: a framework to predict disease severity and stratify patients from clinical data

    Directory of Open Access Journals (Sweden)

    Soumya Banerjee

    2017-10-01

    Full Text Available We outline an automated computational and machine learning framework that predicts disease severity and stratifies patients. We apply our framework to available clinical data. Our algorithm automatically generates insights and predicts disease severity with minimal operator intervention. The computational framework presented here can be used to stratify patients, predict disease severity and propose novel biomarkers for disease. Insights from machine learning algorithms coupled with clinical data may help guide therapy, personalize treatment and help clinicians understand the change in disease over time. Computational techniques like these can be used in translational medicine in close collaboration with clinicians and healthcare providers. Our models are also interpretable, allowing clinicians with minimal machine learning experience to engage in model building. This work is a step towards automated machine learning in the clinic.

  5. Clinical decision making-a functional medicine perspective.

    Science.gov (United States)

    Pizzorno, Joseph E

    2012-09-01

    As 21st century health care moves from a disease-based approach to a more patient-centric system that can address biochemical individuality to improve health and function, clinical decision making becomes more complex. Accentuating the problem is the lack of a clear standard for this more complex functional medicine approach. While there is relatively broad agreement in Western medicine for what constitutes competent assessment of disease and identification of related treatment approaches, the complex functional medicine model posits multiple and individualized diagnostic and therapeutic approaches, most or many of which have reasonable underlying science and principles, but which have not been rigorously tested in a research or clinical setting. This has led to non-rigorous thinking and sometimes to uncritical acceptance of both poorly documented diagnostic procedures and ineffective therapies, resulting in less than optimal clinical care.

  6. A Clinical Decision Support System for Breast Cancer Patients

    Science.gov (United States)

    Fernandes, Ana S.; Alves, Pedro; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Lisboa, Paulo J. G.

    This paper proposes a Web clinical decision support system for clinical oncologists and for breast cancer patients making prognostic assessments, using the particular characteristics of the individual patient. This system comprises three different prognostic modelling methodologies: the clinically widely used Nottingham prognostic index (NPI); the Cox regression modelling and a partial logistic artificial neural network with automatic relevance determination (PLANN-ARD). All three models yield a different prognostic index that can be analysed together in order to obtain a more accurate prognostic assessment of the patient. Missing data is incorporated in the mentioned models, a common issue in medical data that was overcome using multiple imputation techniques. Risk group assignments are also provided through a methodology based on regression trees, where Boolean rules can be obtained expressed with patient characteristics.

  7. Applying Probabilistic Decision Models to Clinical Trial Design

    Science.gov (United States)

    Smith, Wade P; Phillips, Mark H

    2018-01-01

    Clinical trial design most often focuses on a single or several related outcomes with corresponding calculations of statistical power. We consider a clinical trial to be a decision problem, often with competing outcomes. Using a current controversy in the treatment of HPV-positive head and neck cancer, we apply several different probabilistic methods to help define the range of outcomes given different possible trial designs. Our model incorporates the uncertainties in the disease process and treatment response and the inhomogeneities in the patient population. Instead of expected utility, we have used a Markov model to calculate quality adjusted life expectancy as a maximization objective. Monte Carlo simulations over realistic ranges of parameters are used to explore different trial scenarios given the possible ranges of parameters. This modeling approach can be used to better inform the initial trial design so that it will more likely achieve clinical relevance.

  8. Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

    Science.gov (United States)

    Basit, Mujeeb A; Baldwin, Krystal L; Kannan, Vaishnavi; Flahaven, Emily L; Parks, Cassandra J; Ott, Jason M; Willett, Duwayne L

    2018-04-13

    Moving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements." We aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse). Acceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test

  9. Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.

    Science.gov (United States)

    Islam, Roosan; Weir, Charlene R; Jones, Makoto; Del Fiol, Guilherme; Samore, Matthew H

    2015-11-30

    Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases. The cognitive strategies to deal with decision complexity found in this study have important

  10. Medical students, clinical preventive services, and shared decision-making.

    Science.gov (United States)

    Keefe, Carole W; Thompson, Margaret E; Noel, Mary Margaret

    2002-11-01

    Improving access to preventive care requires addressing patient, provider, and systems barriers. Patients often lack knowledge or are skeptical about the importance of prevention. Physicians feel that they have too little time, are not trained to deliver preventive services, and are concerned about the effectiveness of prevention. We have implemented an educational module in the required family practice clerkship (1) to enhance medical student learning about common clinical preventive services and (2) to teach students how to inform and involve patients in shared decision making about those services. Students are asked to examine available evidence-based information for preventive screening services. They are encouraged to look at the recommendations of various organizations and use such resources as reports from the U.S. Preventive Services Task Force to determine recommendations they want to be knowledgeable about in talking with their patients. For learning shared decision making, students are trained to use a model adapted from Braddock and colleagues(1) to discuss specific screening services and to engage patients in the process of making informed decisions about what is best for their own health. The shared decision making is presented and modeled by faculty, discussed in small groups, and students practice using Web-based cases and simulations. The students are evaluated using formative and summative performance-based assessments as they interact with simulated patients about (1) screening for high blood cholesterol and other lipid abnormalities, (2) screening for colorectal cancer, (3) screening for prostate cancer, and (4) screening for breast cancer. The final student evaluation is a ten-minute, videotaped discussion with a simulated patient about screening for colorectal cancer that is graded against a checklist that focuses primarily on the elements of shared decision making. Our medical students appear quite willing to accept shared decision making as

  11. Clinical decision support must be useful, functional is not enough

    DEFF Research Database (Denmark)

    Kortteisto, Tiina; Komulainen, Jorma; Mäkelä, Marjukka

    2012-01-01

    the use of computer-based clinical decision support (eCDS) in primary care and how different professional groups experience it. Our aim was to describe specific reasons for using or not using eCDS among primary care professionals. METHODS: The setting was a Finnish primary health care organization with 48......ABSTRACT: BACKGROUND: Health information technology, particularly electronic decision support systems, can reduce the existing gap between evidence-based knowledge and health care practice but professionals have to accept and use this information. Evidence is scant on which features influence...... professionals receiving patient-specific guidance at the point of care. Multiple data (focus groups, questionnaire and spontaneous feedback) were analyzed using deductive content analysis and descriptive statistics. RESULTS: The content of the guidance is a significant feature of the primary care professional...

  12. Clinical and genetic correlates of decision making in anorexia nervosa.

    Science.gov (United States)

    Tenconi, Elena; Degortes, Daniela; Clementi, Maurizio; Collantoni, Enrico; Pinato, Claudia; Forzan, Monica; Cassina, Matteo; Santonastaso, Paolo; Favaro, Angela

    2016-01-01

    Decision-making (DM) abilities have been found to be impaired in anorexia nervosa (AN), but few data are available about the characteristics and correlates of this cognitive function. The aim of the present study was to provide data on DM functioning in AN using both veridical and adaptive paradigms. While in veridical DM tasks, the individual's ability to predict a true/false response is measured, adaptive DM is the ability to consider both internal and external demands in order to make a good choice, in the absence of a single true "correct" answer. The participants were 189 women, of whom 91 were eating-disordered patients with a lifetime diagnosis of anorexia nervosa, and 98 were healthy women. All the participants underwent clinical, neuropsychological, and genetic assessment. The cognitive evaluation included a set of neuropsychological tasks and two decision-making tests: The Iowa Gambling Task and the Cognitive Bias Task. Anorexia nervosa patients showed significantly poorer performances on both decision-making tasks than healthy women. The Cognitive Bias Task revealed that anorexia nervosa patients employed significantly more context-independent decision-making strategies, which were independent from diagnostic subtype, handedness, education, and psychopathology. In the whole sample (patients and controls), Cognitive Bias Task performance was independently predicted by lifetime anorexia nervosa diagnosis, body mass index at assessment, and 5-HTTLPR genotype. Patients displayed poor decision-making functioning in both veridical and adaptive situations. The difficulties detected in anorexia nervosa individuals may affect not only the ability to consider the future outcomes of their actions (leading to "myopia for the future"), but also the capacity to update and review one's own mindset according to new environmental stimuli.

  13. A bench-top automated workstation for nucleic acid isolation from clinical sample types.

    Science.gov (United States)

    Thakore, Nitu; Garber, Steve; Bueno, Arial; Qu, Peter; Norville, Ryan; Villanueva, Michael; Chandler, Darrell P; Holmberg, Rebecca; Cooney, Christopher G

    2018-04-18

    Systems that automate extraction of nucleic acid from cells or viruses in complex clinical matrices have tremendous value even in the absence of an integrated downstream detector. We describe our bench-top automated workstation that integrates our previously-reported extraction method - TruTip - with our newly-developed mechanical lysis method. This is the first report of this method for homogenizing viscous and heterogeneous samples and lysing difficult-to-disrupt cells using "MagVor": a rotating magnet that rotates a miniature stir disk amidst glass beads confined inside of a disposable tube. Using this system, we demonstrate automated nucleic acid extraction from methicillin-resistant Staphylococcus aureus (MRSA) in nasopharyngeal aspirate (NPA), influenza A in nasopharyngeal swabs (NPS), human genomic DNA from whole blood, and Mycobacterium tuberculosis in NPA. The automated workstation yields nucleic acid with comparable extraction efficiency to manual protocols, which include commercially-available Qiagen spin column kits, across each of these sample types. This work expands the scope of applications beyond previous reports of TruTip to include difficult-to-disrupt cell types and automates the process, including a method for removal of organics, inside a compact bench-top workstation. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Directory of Open Access Journals (Sweden)

    Tiago OLIVEIRA

    2012-09-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The prevalence of situations of medical error and defensive medicine in healthcare institutions is a great concern of the medical community. Clinical Practice Guidelines are regarded by most researchers as a way to mitigate theseoccurrences; however, there is a need to make them interactive, easier to update and to deploy. This paper provides a model for Computer-Interpretable Guidelines based on the generic tasks of the clinical process, devised to be included in the framework of a Clinical Decision Support System. Aiming to represent medical recommendations in a simple and intuitive way. Hence, this work proposes a knowledge representation formalism that uses an Extension to Logic Programming to handle incomplete information. This model is used to represent different cases of missing, conflicting and inexact information with the aid of a method to quantify its quality. The integration of the guideline model with the knowledge representation formalism yields a clinical decision model that relies on the development of multiple information scenarios and the exploration of different clinical hypotheses.

  15. Guideline Formalization and Knowledge Representation for Clinical Decision Support

    Directory of Open Access Journals (Sweden)

    Paulo NOVAIS

    2013-07-01

    Full Text Available Normal 0 21 false false false EN-US JA X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The prevalence of situations of medical error and defensive medicine in healthcare institutions is a great concern of the medical community. Clinical Practice Guidelines are regarded by most researchers as a way to mitigate these occurrences; however, there is a need to make them interactive, easier to update and to deploy. This paper provides a model for Computer-Interpretable Guidelines based on the generic tasks of the clinical process, devised to be included in the framework of a Clinical Decision Support System. Aiming to represent medical recommendations in a simple and intuitive way. Hence, this work proposes a knowledge representation formalism that uses an Extension to Logic Programming to handle incomplete information. This model is used to represent different cases of missing, conflicting and inexact information with the aid of a method to quantify its quality. The integration of the guideline model with the knowledge representation formalism yields a clinical decision model that relies on the development of multiple information scenarios and the exploration of different clinical hypotheses.

  16. Clinical decision-making and secondary findings in systems medicine.

    Science.gov (United States)

    Fischer, T; Brothers, K B; Erdmann, P; Langanke, M

    2016-05-21

    Systems medicine is the name for an assemblage of scientific strategies and practices that include bioinformatics approaches to human biology (especially systems biology); "big data" statistical analysis; and medical informatics tools. Whereas personalized and precision medicine involve similar analytical methods applied to genomic and medical record data, systems medicine draws on these as well as other sources of data. Given this distinction, the clinical translation of systems medicine poses a number of important ethical and epistemological challenges for researchers working to generate systems medicine knowledge and clinicians working to apply it. This article focuses on three key challenges: First, we will discuss the conflicts in decision-making that can arise when healthcare providers committed to principles of experimental medicine or evidence-based medicine encounter individualized recommendations derived from computer algorithms. We will explore in particular whether controlled experiments, such as comparative effectiveness trials, should mediate the translation of systems medicine, or if instead individualized findings generated through "big data" approaches can be applied directly in clinical decision-making. Second, we will examine the case of the Riyadh Intensive Care Program Mortality Prediction Algorithm, pejoratively referred to as the "death computer," to demonstrate the ethical challenges that can arise when big-data-driven scoring systems are applied in clinical contexts. We argue that the uncritical use of predictive clinical algorithms, including those envisioned for systems medicine, challenge basic understandings of the doctor-patient relationship. Third, we will build on the recent discourse on secondary findings in genomics and imaging to draw attention to the important implications of secondary findings derived from the joint analysis of data from diverse sources, including data recorded by patients in an attempt to realize their

  17. Is it the time to rethink clinical decision-making strategies? From a single clinical outcome evaluation to a Clinical Multi-criteria Decision Assessment (CMDA).

    Science.gov (United States)

    Migliore, Alberto; Integlia, Davide; Bizzi, Emanuele; Piaggio, Tomaso

    2015-10-01

    There are plenty of different clinical, organizational and economic parameters to consider in order having a complete assessment of the total impact of a pharmaceutical treatment. In the attempt to follow, a holistic approach aimed to provide an evaluation embracing all clinical parameters in order to choose the best treatments, it is necessary to compare and weight multiple criteria. Therefore, a change is required: we need to move from a decision-making context based on the assessment of one single criteria towards a transparent and systematic framework enabling decision makers to assess all relevant parameters simultaneously in order to choose the best treatment to use. In order to apply the MCDA methodology to clinical decision making the best pharmaceutical treatment (or medical devices) to use to treat a specific pathology, we suggest a specific application of the Multiple Criteria Decision Analysis for the purpose, like a Clinical Multi-criteria Decision Assessment CMDA. In CMDA, results from both meta-analysis and observational studies are used by a clinical consensus after attributing weights to specific domains and related parameters. The decision will result from a related comparison of all consequences (i.e., efficacy, safety, adherence, administration route) existing behind the choice to use a specific pharmacological treatment. The match will yield a score (in absolute value) that link each parameter with a specific intervention, and then a final score for each treatment. The higher is the final score; the most appropriate is the intervention to treat disease considering all criteria (domain an parameters). The results will allow the physician to evaluate the best clinical treatment for his patients considering at the same time all relevant criteria such as clinical effectiveness for all parameters and administration route. The use of CMDA model will yield a clear and complete indication of the best pharmaceutical treatment to use for patients

  18. Automation of the consensus guidelines in diabetes care: potential impact on clinical inertia.

    Science.gov (United States)

    Albisser, A Michael; Inhaber, Francine

    2010-01-01

    To propose that automation of the consensus guidelines and mandated targets (CG&MT) in glycemia, hemoglobin A1c, and body weight will facilitate optimal clinical management of patients with diabetes. (1) A simplified method for capturing diabetes outcomes at home was devised, (2) relevant portions of the CG&MT were translated into computer code and automated, and (3) algorithms were applied to transform data from self-monitoring of blood glucose into circadian profiles and hemoglobin A1c levels. (4) The resulting procedures were integrated into a USB memory drive for use by health-care providers at the point of care. For input from patients, a simple form is used to capture data on diabetes outcomes, including blood glucose measurements before and after meals and at bedtime, medication, and lifestyle events in a structured fashion. At each encounter with a health-care provider, the patient's data are transferred into the device and become available to assist in identifying deviations from mandated targets, potential risks of hypoglycemia, and necessary prescription changes. Preliminary observations during a 2 1/2-year period from a community support group dedicated to glycemic control on 20 unselected patients (10 with and 10 without use of the device) are summarized. With use of the automated information, the health professional is supported at the point of care to achieve better, safer outcomes and practice evidence-based medicine entirely in lockstep with the CG&MT. This automation helps to overcome clinical inertia.

  19. Transforming clinical practice guidelines and clinical pathways into fast-and-frugal decision trees to improve clinical care strategies.

    Science.gov (United States)

    Djulbegovic, Benjamin; Hozo, Iztok; Dale, William

    2018-02-27

    Contemporary delivery of health care is inappropriate in many ways, largely due to suboptimal Q5 decision-making. A typical approach to improve practitioners' decision-making is to develop evidence-based clinical practice guidelines (CPG) by guidelines panels, who are instructed to use their judgments to derive practice recommendations. However, mechanisms for the formulation of guideline judgments remains a "black-box" operation-a process with defined inputs and outputs but without sufficient knowledge of its internal workings. Increased explicitness and transparency in the process can be achieved by implementing CPG as clinical pathways (CPs) (also known as clinical algorithms or flow-charts). However, clinical recommendations thus derived are typically ad hoc and developed by experts in a theory-free environment. As any recommendation can be right (true positive or negative), or wrong (false positive or negative), the lack of theoretical structure precludes the quantitative assessment of the management strategies recommended by CPGs/CPs. To realize the full potential of CPGs/CPs, they need to be placed on more solid theoretical grounds. We believe this potential can be best realized by converting CPGs/CPs within the heuristic theory of decision-making, often implemented as fast-and-frugal (FFT) decision trees. This is possible because FFT heuristic strategy of decision-making can be linked to signal detection theory, evidence accumulation theory, and a threshold model of decision-making, which, in turn, allows quantitative analysis of the accuracy of clinical management strategies. Fast-and-frugal provides a simple and transparent, yet solid and robust, methodological framework connecting decision science to clinical care, a sorely needed missing link between CPGs/CPs and patient outcomes. We therefore advocate that all guidelines panels express their recommendations as CPs, which in turn should be converted into FFTs to guide clinical care. © 2018 John Wiley

  20. Clinical Decision Support Knowledge Management: Strategies for Success.

    Science.gov (United States)

    Khalifa, Mohamed; Alswailem, Osama

    2015-01-01

    Clinical Decision Support Systems have been shown to increase quality of care, patient safety, improve adherence to guidelines for prevention and treatment, and avoid medication errors. Such systems depend mainly on two types of content; the clinical information related to patients and the medical knowledge related to the specialty that informs the system rules and alerts. At King Faisal Specialist Hospital and Research Center, Saudi Arabia, the Health Information Technology Affairs worked on identifying best strategies and recommendations for successful CDSS knowledge management. A review of literature was conducted to identify main areas of challenges and factors of success. A qualitative survey was used over six months' duration to collect opinions, experiences and suggestions from both IT and healthcare professionals. Recommendations were categorized into ten main topics that should be addressed during the development and implementation of CDSS knowledge management tools in the hospital.

  1. Evaluation of RxNorm for Medication Clinical Decision Support.

    Science.gov (United States)

    Freimuth, Robert R; Wix, Kelly; Zhu, Qian; Siska, Mark; Chute, Christopher G

    2014-01-01

    We evaluated the potential use of RxNorm to provide standardized representations of generic drug name and route of administration to facilitate management of drug lists for clinical decision support (CDS) rules. We found a clear representation of generic drug name but not route of administration. We identified several issues related to data quality, including erroneous or missing defined relationships, and the use of different concept hierarchies to represent the same drug. More importantly, we found extensive semantic precoordination of orthogonal concepts related to route and dose form, which would complicate the use of RxNorm for drug-based CDS. This study demonstrated that while RxNorm is a valuable resource for the standardization of medications used in clinical practice, additional work is required to enhance the terminology so that it can support expanded use cases, such as managing drug lists for CDS.

  2. Implications of caries diagnostic strategies for clinical management decisions

    DEFF Research Database (Denmark)

    Baelum, Vibeke; Hintze, Hanne; Wenzel, Ann

    2012-01-01

    -specificity) were calculated for each diagnostic strategy. RESULTS: Visual-tactile examination provided a true-positive rate of 34.2% and a false-positive rate of 1.5% for the detection of a cavity. The combination of a visual-tactile and a radiographic examination using the lesion in dentin threshold......OBJECTIVES: In clinical practice, a visual-tactile caries examination is frequently supplemented by bitewing radiography. This study evaluated strategies for combining visual-tactile and radiographic caries detection methods and determined their implications for clinical management decisions...... and cavitated lesions while the radiographic examination determined lesion depth. Direct inspection of the surfaces following tooth separation for the presence of cavitated or noncavitated lesions was the validation method. The true-positive rate (i.e. the sensitivity) and the false-positive rate (i.e. 1...

  3. A mathematical model for interpretable clinical decision support with applications in gynecology.

    Directory of Open Access Journals (Sweden)

    Vanya M C A Van Belle

    Full Text Available Over time, methods for the development of clinical decision support (CDS systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models. The resulting models can be used to guide clinicians when deciding upon the appropriate treatment, estimating patient-specific risks and to improve communication with patients.We propose the interval coded scoring (ICS system, which imposes that the effect of each variable on the estimated risk is constant within consecutive intervals. The number and position of the intervals are automatically obtained by solving an optimization problem, which additionally performs variable selection. The resulting model can be visualised by means of appealing scoring tables and color bars. ICS models can be used within software packages, in smartphone applications, or on paper, which is particularly useful for bedside medicine and home-monitoring. The ICS approach is illustrated on two gynecological problems: diagnosis of malignancy of ovarian tumors using a dataset containing 3,511 patients, and prediction of first trimester viability of pregnancies using a dataset of 1,435 women. Comparison of the performance of the ICS approach with a range of prediction models proposed in the literature illustrates the ability of ICS to combine optimal performance with the interpretability of simple scoring systems.The ICS approach can improve patient-clinician communication and will provide additional insights in the importance and influence of available variables. Future challenges include extensions of the

  4. Impact of a Clinical Decision Support System on Pharmacy Clinical Interventions, Documentation Efforts, and Costs

    OpenAIRE

    Calloway, Stacy; Akilo, Hameed A.; Bierman, Kyle

    2013-01-01

    Health care organizations are turning to electronic clinical decision support systems (CDSSs) to increase quality of patient care and promote a safer environment. A CDSS is a promising approach to the aggregation and use of patient data to identify patients who would most benefit from interventions by pharmacy clinicians. However, there are limited published reports describing the impact of CDSS on clinical pharmacy measures. In February 2011, Good Shepherd Medical Center, a 425-bed acute car...

  5. Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

    Science.gov (United States)

    Bennett, Casey C; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal

  6. The Manchester Acute Coronary Syndromes (MACS) decision rule: validation with a new automated assay for heart-type fatty acid binding protein.

    Science.gov (United States)

    Body, Richard; Burrows, Gillian; Carley, Simon; Lewis, Philip S

    2015-10-01

    The Manchester Acute Coronary Syndromes (MACS) decision rule may enable acute coronary syndromes to be immediately 'ruled in' or 'ruled out' in the emergency department. The rule incorporates heart-type fatty acid binding protein (h-FABP) and high sensitivity troponin T levels. The rule was previously validated using a semiautomated h-FABP assay that was not practical for clinical implementation. We aimed to validate the rule with an automated h-FABP assay that could be used clinically. In this prospective diagnostic cohort study we included patients presenting to the emergency department with suspected cardiac chest pain. Serum drawn on arrival was tested for h-FABP using an automated immunoturbidimetric assay (Randox) and high sensitivity troponin T (Roche). The primary outcome, a diagnosis of acute myocardial infarction (AMI), was adjudicated based on 12 h troponin testing. A secondary outcome, major adverse cardiac events (MACE; death, AMI, revascularisation or new coronary stenosis), was determined at 30 days. Of the 456 patients included, 78 (17.1%) had AMI and 97 (21.3%) developed MACE. Using the automated h-FABP assay, the MACS rule had the same C-statistic for MACE as the original rule (0.91; 95% CI 0.88 to 0.92). 18.9% of patients were identified as 'very low risk' and thus eligible for immediate discharge with no missed AMIs and a 2.3% incidence of MACE (n=2, both coronary stenoses). 11.1% of patients were classed as 'high-risk' and had a 92.0% incidence of MACE. Our findings validate the performance of a refined MACS rule incorporating an automated h-FABP assay, facilitating use in clinical settings. The effectiveness of this refined rule should be verified in an interventional trial prior to implementation. UK CRN 8376. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  7. Monitoring, accounting and automated decision support for the ALICE experiment based on the MonALISA framework

    CERN Document Server

    Cirstoiu, C; Betev, L; Saiz, P; Peters, A J; Muraru, A; Voicu, R; Legrand, I

    2007-01-01

    We are developing a general purpose monitoring system for the ALICE experiment, based on the MonALISA framework. MonALISA (Monitoring Agents using a Large Integrated Services Architecture) is a fully distributed system with no single point of failure that is able to collect, store monitoring information and present it as significant perspectives and synthetic views on the status and the trends of the entire system. Furthermore, agents can use it for taking automated operational decisions. Monitoring information is gathered locally from all the components running in each site. The entire flow of information is aggregated on site level by a MonALISA service and then collected and presented in various forms by a central MonALISA Repository. Based on this information, other services take operational decisions such as alerts, triggers, service restarts and automatic production job or transfer submissions. The system monitors all the components: computer clusters (all major parameters of each computing node), jobs ...

  8. Are patient decision aids the best way to improve clinical decision making? Report of the IPDAS Symposium.

    Science.gov (United States)

    Holmes-Rovner, Margaret; Nelson, Wendy L; Pignone, Michael; Elwyn, Glyn; Rovner, David R; O'Connor, Annette M; Coulter, Angela; Correa-de-Araujo, Rosaly

    2007-01-01

    This article reports on the International Patient Decision Aid Standards Symposium held in 2006 at the annual meeting of the Society for Medical Decision Making in Cambridge, Massachusetts. The symposium featured a debate regarding the proposition that "decision aids are the best way to improve clinical decision making.'' The formal debate addressed the theoretical problem of the appropriate gold standard for an improved decision, efficacy of decision aids, and prospects for implementation. Audience comments and questions focused on both theory and practice: the often unacknowledged roots of decision aids in expected utility theory and the practical problems of limited patient decision aid implementation in health care. The participants' vote on the proposition was approximately half for and half against.

  9. Automated Creation of Datamarts from a Clinical Data Warehouse, Driven by an Active Metadata Repository

    Science.gov (United States)

    Rogerson, Charles L.; Kohlmiller, Paul H.; Stutman, Harris

    1998-01-01

    A methodology and toolkit are described which enable the automated metadata-driven creation of datamarts from clinical data warehouses. The software uses schema-to-schema transformation driven by an active metadata repository. Tools for assessing datamart data quality are described, as well as methods for assessing the feasibility of implementing specific datamarts. A methodology for data remediation and the re-engineering of operational data capture is described.

  10. Automated Text Messaging as an Adjunct to Cognitive Behavioral Therapy for Depression: A Clinical Trial

    OpenAIRE

    Aguilera, Adrian; Bruehlman-Senecal, Emma; Demasi, Orianna; Avila, Patricia

    2017-01-01

    Background: Cognitive Behavioral Therapy (CBT) for depression is efficacious, but effectiveness is limited when implemented in low-income settings due to engagement difficulties including nonadherence with skill-building homework and early discontinuation of treatment. Automated messaging can be used in clinical settings to increase dosage of depression treatment and encourage sustained engagement with psychotherapy. Objectives: The aim of this study was to test whether a text messag...

  11. A semi-automated tool for treatment plan-quality evaluation and clinical trial quality assurance

    Science.gov (United States)

    Wang, Jiazhou; Chen, Wenzhou; Studenski, Matthew; Cui, Yunfeng; Lee, Andrew J.; Xiao, Ying

    2013-07-01

    The goal of this work is to develop a plan-quality evaluation program for clinical routine and multi-institutional clinical trials so that the overall evaluation efficiency is improved. In multi-institutional clinical trials evaluating the plan quality is a time-consuming and labor-intensive process. In this note, we present a semi-automated plan-quality evaluation program which combines MIMVista, Java/MATLAB, and extensible markup language (XML). More specifically, MIMVista is used for data visualization; Java and its powerful function library are implemented for calculating dosimetry parameters; and to improve the clarity of the index definitions, XML is applied. The accuracy and the efficiency of the program were evaluated by comparing the results of the program with the manually recorded results in two RTOG trials. A slight difference of about 0.2% in volume or 0.6 Gy in dose between the semi-automated program and manual recording was observed. According to the criteria of indices, there are minimal differences between the two methods. The evaluation time is reduced from 10-20 min to 2 min by applying the semi-automated plan-quality evaluation program.

  12. A semi-automated tool for treatment plan-quality evaluation and clinical trial quality assurance

    International Nuclear Information System (INIS)

    Wang, Jiazhou; Chen, Wenzhou; Studenski, Matthew; Cui, Yunfeng; Xiao, Ying; Lee, Andrew J

    2013-01-01

    The goal of this work is to develop a plan-quality evaluation program for clinical routine and multi-institutional clinical trials so that the overall evaluation efficiency is improved. In multi-institutional clinical trials evaluating the plan quality is a time-consuming and labor-intensive process. In this note, we present a semi-automated plan-quality evaluation program which combines MIMVista, Java/MATLAB, and extensible markup language (XML). More specifically, MIMVista is used for data visualization; Java and its powerful function library are implemented for calculating dosimetry parameters; and to improve the clarity of the index definitions, XML is applied. The accuracy and the efficiency of the program were evaluated by comparing the results of the program with the manually recorded results in two RTOG trials. A slight difference of about 0.2% in volume or 0.6 Gy in dose between the semi-automated program and manual recording was observed. According to the criteria of indices, there are minimal differences between the two methods. The evaluation time is reduced from 10–20 min to 2 min by applying the semi-automated plan-quality evaluation program. (note)

  13. The Value of Information in Automated Negotiation: A Decision Model for Eliciting User Preferences

    NARCIS (Netherlands)

    T. Baarslag (Tim); M. Kaisers (Michael)

    2017-01-01

    textabstractConsider an agent that can autonomously negotiate and coordinate with others in our stead, to reach outcomes and agreements in our interest. Such automated negotiation agents are already common practice in areas such as high frequency trading, and are now finding applications in domains

  14. Clinical implementation of RNA signatures for pharmacogenomic decision-making

    Directory of Open Access Journals (Sweden)

    Tang W

    2011-09-01

    Full Text Available Weihua Tang1, Zhiyuan Hu2, Hind Muallem1, Margaret L Gulley1,21Department of Pathology and Laboratory Medicine, 2Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, North Carolina, NC, USAAbstract: RNA profiling is increasingly used to predict drug response, dose, or toxicity based on analysis of drug pharmacokinetic or pharmacodynamic pathways. Before implementing multiplexed RNA arrays in clinical practice, validation studies are carried out to demonstrate sufficient evidence of analytic and clinical performance, and to establish an assay protocol with quality assurance measures. Pathologists assure quality by selecting input tissue and by interpreting results in the context of the input tissue as well as the technologies that were used and the clinical setting in which the test was ordered. A strength of RNA profiling is the array-based measurement of tens to thousands of RNAs at once, including redundant tests for critical analytes or pathways to promote confidence in test results. Instrument and reagent manufacturers are crucial for supplying reliable components of the test system. Strategies for quality assurance include careful attention to RNA preservation and quality checks at pertinent steps in the assay protocol, beginning with specimen collection and proceeding through the various phases of transport, processing, storage, analysis, interpretation, and reporting. Specimen quality is checked by probing housekeeping transcripts, while spiked and exogenous controls serve as a check on analytic performance of the test system. Software is required to manipulate abundant array data and present it for interpretation by a laboratory physician who reports results in a manner facilitating therapeutic decision-making. Maintenance of the assay requires periodic documentation of personnel competency and laboratory proficiency. These strategies are shepherding genomic arrays into clinical settings to provide added

  15. Remote clinical decision-making: a clinician's definition.

    Science.gov (United States)

    Brady, Mike; Northstone, Kate

    2017-05-12

    Aims Remote clinical decision-making (RCDM), commonly known as 'telephone triage' or 'hear and treat', describes clinicians' non-face-to-face involvement with patient care, and is an established strategy in UK ambulance services for managing increasing demand. However, there is no suitable definition of RCDM that fully explains the roles undertaken by clinicians in 999 hubs, or for its use as an ambulance quality indicator (AQI). The aim of this study, which is part of a larger evaluation of a new RCDM module in higher education, is to determine how clinicians define RCDM. Methods Three participants were asked, during semi-structured interviews, to define RCDM. The interviews were recorded, transcribed and thematically analysed. Results Clinicians do not focus on outcomes when defining RCDM, but on the efficacy of the process and the appropriateness of the determined outcome. Conclusion There is no precise description of the role of healthcare professionals in 999 clinical hubs, but there is a need for role clarity, for employees and organisations. The study questions the suitability of the definition of hear and treat as an AQI, as it does not appear to represent fully the various duties undertaken by 999 clinical hub healthcare professionals. More research is needed to consider the definition of RCDM in all its forms.

  16. Peripheral Exophytic Oral Lesions: A Clinical Decision Tree

    Directory of Open Access Journals (Sweden)

    Hamed Mortazavi

    2017-01-01

    Full Text Available Diagnosis of peripheral oral exophytic lesions might be quite challenging. This review article aimed to introduce a decision tree for oral exophytic lesions according to their clinical features. General search engines and specialized databases including PubMed, PubMed Central, Medline Plus, EBSCO, Science Direct, Scopus, Embase, and authenticated textbooks were used to find relevant topics by means of keywords such as “oral soft tissue lesion,” “oral tumor like lesion,” “oral mucosal enlargement,” and “oral exophytic lesion.” Related English-language articles published since 1988 to 2016 in both medical and dental journals were appraised. Upon compilation of data, peripheral oral exophytic lesions were categorized into two major groups according to their surface texture: smooth (mesenchymal or nonsquamous epithelium-originated and rough (squamous epithelium-originated. Lesions with smooth surface were also categorized into three subgroups according to their general frequency: reactive hyperplastic lesions/inflammatory hyperplasia, salivary gland lesions (nonneoplastic and neoplastic, and mesenchymal lesions (benign and malignant neoplasms. In addition, lesions with rough surface were summarized in six more common lesions. In total, 29 entities were organized in the form of a decision tree in order to help clinicians establish a logical diagnosis by a stepwise progression method.

  17. Duplicate laboratory test reduction using a clinical decision support tool.

    Science.gov (United States)

    Procop, Gary W; Yerian, Lisa M; Wyllie, Robert; Harrison, A Marc; Kottke-Marchant, Kandice

    2014-05-01

    Duplicate laboratory tests that are unwarranted increase unnecessary phlebotomy, which contributes to iatrogenic anemia, decreased patient satisfaction, and increased health care costs. We employed a clinical decision support tool (CDST) to block unnecessary duplicate test orders during the computerized physician order entry (CPOE) process. We assessed laboratory cost savings after 2 years and searched for untoward patient events associated with this intervention. This CDST blocked 11,790 unnecessary duplicate test orders in these 2 years, which resulted in a cost savings of $183,586. There were no untoward effects reported associated with this intervention. The movement to CPOE affords real-time interaction between the laboratory and the physician through CDSTs that signal duplicate orders. These interactions save health care dollars and should also increase patient satisfaction and well-being.

  18. Optimizing perioperative decision making: improved information for clinical workflow planning.

    Science.gov (United States)

    Doebbeling, Bradley N; Burton, Matthew M; Wiebke, Eric A; Miller, Spencer; Baxter, Laurence; Miller, Donald; Alvarez, Jorge; Pekny, Joseph

    2012-01-01

    Perioperative care is complex and involves multiple interconnected subsystems. Delayed starts, prolonged cases and overtime are common. Surgical procedures account for 40-70% of hospital revenues and 30-40% of total costs. Most planning and scheduling in healthcare is done without modern planning tools, which have potential for improving access by assisting in operations planning support. We identified key planning scenarios of interest to perioperative leaders, in order to examine the feasibility of applying combinatorial optimization software solving some of those planning issues in the operative setting. Perioperative leaders desire a broad range of tools for planning and assessing alternate solutions. Our modeled solutions generated feasible solutions that varied as expected, based on resource and policy assumptions and found better utilization of scarce resources. Combinatorial optimization modeling can effectively evaluate alternatives to support key decisions for planning clinical workflow and improving care efficiency and satisfaction.

  19. An Automated and Intelligent Medical Decision Support System for Brain MRI Scans Classification.

    Directory of Open Access Journals (Sweden)

    Muhammad Faisal Siddiqui

    Full Text Available A wide interest has been observed in the medical health care applications that interpret neuroimaging scans by machine learning systems. This research proposes an intelligent, automatic, accurate, and robust classification technique to classify the human brain magnetic resonance image (MRI as normal or abnormal, to cater down the human error during identifying the diseases in brain MRIs. In this study, fast discrete wavelet transform (DWT, principal component analysis (PCA, and least squares support vector machine (LS-SVM are used as basic components. Firstly, fast DWT is employed to extract the salient features of brain MRI, followed by PCA, which reduces the dimensions of the features. These reduced feature vectors also shrink the memory storage consumption by 99.5%. At last, an advanced classification technique based on LS-SVM is applied to brain MR image classification using reduced features. For improving the efficiency, LS-SVM is used with non-linear radial basis function (RBF kernel. The proposed algorithm intelligently determines the optimized values of the hyper-parameters of the RBF kernel and also applied k-fold stratified cross validation to enhance the generalization of the system. The method was tested by 340 patients' benchmark datasets of T1-weighted and T2-weighted scans. From the analysis of experimental results and performance comparisons, it is observed that the proposed medical decision support system outperformed all other modern classifiers and achieves 100% accuracy rate (specificity/sensitivity 100%/100%. Furthermore, in terms of computation time, the proposed technique is significantly faster than the recent well-known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. These results indicate that the proposed well-trained machine learning system has the potential to make accurate predictions about brain abnormalities

  20. A clinical decision-making algorithm for penicillin allergy.

    Science.gov (United States)

    Soria, Angèle; Autegarden, Elodie; Amsler, Emmanuelle; Gaouar, Hafida; Vial, Amandine; Francès, Camille; Autegarden, Jean-Eric

    2017-12-01

    About 10% of subjects report suspected penicillin allergy, but 85-90% of these patients are not truly allergic and could safely receive beta-lactam antibiotics Objective: To design and validate a clinical decision-making algorithm, based on anamnesis (chronology, severity, and duration of the suspected allergic reactions) and reaching a 100% sensitivity and negative predictive value, to assess allergy risk related to a penicillin prescription in general practise. All patients were included prospectively and explorated based on ENDA/EAACI recommendations. Results of penicillin allergy work-up (gold standard) were compared with results of the algorithm. Allergological work-up diagnosed penicillin hypersensitivity in 41/259 patients (15.8%) [95% CI: 11.5-20.3]. Three of these patients were diagnosed as having immediate-type hypersensitivity to penicillin, but had been misdiagnosed as low risk patients using the clinical algorithm. Thus, the sensitivity and negative predictive value of the algorithm were 92.7% [95% CI: 80.1-98.5] and 96.3% [95% CI: 89.6-99.2], respectively, and the probability that a patient with true penicillin allergy had been misclassified was 3.7% [95% CI: 0.8-10.4]. Although the risk of misclassification is low, we cannot recommend the use of this algorithm in general practice. However, the algorithm can be useful in emergency situations in hospital settings. Key messages True penicillin allergy is considerably lower than alleged penicillin allergy (15.8%; 41 of the 259 patients with suspected penicillin allergy). A clinical algorithm based on the patient's clinical history of the supposed allergic event to penicillin misclassified 3/41 (3.7%) truly allergic patients.

  1. Evaluation of an automated knowledge-based textual summarization system for longitudinal clinical data, in the intensive care domain.

    Science.gov (United States)

    Goldstein, Ayelet; Shahar, Yuval; Orenbuch, Efrat; Cohen, Matan J

    2017-10-01

    To examine the feasibility of the automated creation of meaningful free-text summaries of longitudinal clinical records, using a new general methodology that we had recently developed; and to assess the potential benefits to the clinical decision-making process of using such a method to generate draft letters that can be further manually enhanced by clinicians. We had previously developed a system, CliniText (CTXT), for automated summarization in free text of longitudinal medical records, using a clinical knowledge base. In the current study, we created an Intensive Care Unit (ICU) clinical knowledge base, assisted by two ICU clinical experts in an academic tertiary hospital. The CTXT system generated free-text summary letters from the data of 31 different patients, which were compared to the respective original physician-composed discharge letters. The main evaluation measures were (1) relative completeness, quantifying the data items missed by one of the letters but included by the other, and their importance; (2) quality parameters, such as readability; (3) functional performance, assessed by the time needed, by three clinicians reading each of the summaries, to answer five key questions, based on the discharge letter (e.g., "What are the patient's current respiratory requirements?"), and by the correctness of the clinicians' answers. Completeness: In 13/31 (42%) of the letters the number of important items missed in the CTXT-generated letter was actually less than or equal to the number of important items missed by the MD-composed letter. In each of the MD-composed letters, at least two important items that were mentioned by the CTXT system were missed (a mean of 7.2±5.74). In addition, the standard deviation in the number of missed items in the MD letters (STD=15.4) was much higher than the standard deviation in the CTXT-generated letters (STD=5.3). Quality: The MD-composed letters obtained a significantly better grade in three out of four measured parameters

  2. Automated astatination of biomolecules - a stepping stone towards multicenter clinical trials

    DEFF Research Database (Denmark)

    Aneheim, Emma; Albertsson, Per; Bäck, Tom

    2015-01-01

    To facilitate multicentre clinical studies on targeted alpha therapy, it is necessary to develop an automated, on-site procedure for conjugating rare, short-lived, alpha-emitting radionuclides to biomolecules. Astatine-211 is one of the few alpha-emitting nuclides with appropriate chemical...... vector, which can guide the radiation to the cancer cells. Consequently, an appropriate method is required for coupling the nuclide to the vector. To increase the availability of astatine-211 radiopharmaceuticals for targeted alpha therapy, their production should be automated. Here, we present a method...... challenging, alpha-emitting radionuclide. In this work, we describe the process platform, and we demonstrate the production of both astaine-211, for preclinical use, and astatine-211 labelled antibodies....

  3. From Value Assessment to Value Cocreation: Informing Clinical Decision-Making with Medical Claims Data.

    Science.gov (United States)

    Thompson, Steven; Varvel, Stephen; Sasinowski, Maciek; Burke, James P

    2016-09-01

    Big data and advances in analytical processes represent an opportunity for the healthcare industry to make better evidence-based decisions on the value generated by various tests, procedures, and interventions. Value-based reimbursement is the process of identifying and compensating healthcare providers based on whether their services improve quality of care without increasing cost of care or maintain quality of care while decreasing costs. In this article, we motivate and illustrate the potential opportunities for payers and providers to collaborate and evaluate the clinical and economic efficacy of different healthcare services. We conduct a case study of a firm that offers advanced biomarker and disease state management services for cardiovascular and cardiometabolic conditions. A value-based analysis that comprised a retrospective case/control cohort design was conducted, and claims data for over 7000 subjects who received these services were compared to a matched control cohort. Study subjects were commercial and Medicare Advantage enrollees with evidence of CHD, diabetes, or a related condition. Analysis of medical claims data showed a lower proportion of patients who received biomarker testing and disease state management services experienced a MI (p companies have in terms of identifying value-creating healthcare interventions. However, payers and providers also need to pursue system integration efforts to further automate the identification and dissemination of clinically and economically efficacious treatment plans to ensure at-risk patients receive the treatments and interventions that will benefit them the most.

  4. Automated Registration of Multimodal Optic Disc Images: Clinical Assessment of Alignment Accuracy.

    Science.gov (United States)

    Ng, Wai Siene; Legg, Phil; Avadhanam, Venkat; Aye, Kyaw; Evans, Steffan H P; North, Rachel V; Marshall, Andrew D; Rosin, Paul; Morgan, James E

    2016-04-01

    To determine the accuracy of automated alignment algorithms for the registration of optic disc images obtained by 2 different modalities: fundus photography and scanning laser tomography. Images obtained with the Heidelberg Retina Tomograph II and paired photographic optic disc images of 135 eyes were analyzed. Three state-of-the-art automated registration techniques Regional Mutual Information, rigid Feature Neighbourhood Mutual Information (FNMI), and nonrigid FNMI (NRFNMI) were used to align these image pairs. Alignment of each composite picture was assessed on a 5-point grading scale: "Fail" (no alignment of vessels with no vessel contact), "Weak" (vessels have slight contact), "Good" (vessels with 50% contact), and "Excellent" (complete alignment). Custom software generated an image mosaic in which the modalities were interleaved as a series of alternate 5×5-pixel blocks. These were graded independently by 3 clinically experienced observers. A total of 810 image pairs were assessed. All 3 registration techniques achieved a score of "Good" or better in >95% of the image sets. NRFNMI had the highest percentage of "Excellent" (mean: 99.6%; range, 95.2% to 99.6%), followed by Regional Mutual Information (mean: 81.6%; range, 86.3% to 78.5%) and FNMI (mean: 73.1%; range, 85.2% to 54.4%). Automated registration of optic disc images by different modalities is a feasible option for clinical application. All 3 methods provided useful levels of alignment, but the NRFNMI technique consistently outperformed the others and is recommended as a practical approach to the automated registration of multimodal disc images.

  5. An Automated Medical Information Management System (OpScan-MIMS) in a Clinical Setting

    Science.gov (United States)

    Margolis, S.; Baker, T.G.; Ritchey, M.G.; Alterescu, S.; Friedman, C.

    1981-01-01

    This paper describes an automated medical information management system within a clinic setting. The system includes an optically scanned data entry system (OpScan), a generalized, interactive retrieval and storage software system(Medical Information Management System, MIMS) and the use of time-sharing. The system has the advantages of minimal hardware purchase and maintenance, rapid data entry and retrieval, user-created programs, no need for user knowledge of computer language or technology and is cost effective. The OpScan-MIMS system has been operational for approximately 16 months in a sexually transmitted disease clinic. The system's application to medical audit, quality assurance, clinic management and clinical training are demonstrated.

  6. Development of a clinical decision model for thyroid nodules

    Directory of Open Access Journals (Sweden)

    Eberhardt John

    2009-08-01

    Full Text Available Abstract Background Thyroid nodules represent a common problem brought to medical attention. Four to seven percent of the United States adult population (10–18 million people has a palpable thyroid nodule, however the majority (>95% of thyroid nodules are benign. While, fine needle aspiration remains the most cost effective and accurate diagnostic tool for thyroid nodules in current practice, over 20% of patients undergoing FNA of a thyroid nodule have indeterminate cytology (follicular neoplasm with associated malignancy risk prevalence of 20–30%. These patients require thyroid lobectomy/isthmusectomy purely for the purpose of attaining a definitive diagnosis. Given that the majority (70–80% of these patients have benign surgical pathology, thyroidectomy in these patients is conducted principally with diagnostic intent. Clinical models predictive of malignancy risk are needed to support treatment decisions in patients with thyroid nodules in order to reduce morbidity associated with unnecessary diagnostic surgery. Methods Data were analyzed from a completed prospective cohort trial conducted over a 4-year period involving 216 patients with thyroid nodules undergoing ultrasound (US, electrical impedance scanning (EIS and fine needle aspiration cytology (FNA prior to thyroidectomy. A Bayesian model was designed to predict malignancy in thyroid nodules based on multivariate dependence relationships between independent covariates. Ten-fold cross-validation was performed to estimate classifier error wherein the data set was randomized into ten separate and unique train and test sets consisting of a training set (90% of records and a test set (10% of records. A receiver-operating-characteristics (ROC curve of these predictions and area under the curve (AUC were calculated to determine model robustness for predicting malignancy in thyroid nodules. Results Thyroid nodule size, FNA cytology, US and EIS characteristics were highly predictive of

  7. Appreciative inquiry enhances cardiology nurses’ clinical decision making when using a clinical guideline on delirium

    DEFF Research Database (Denmark)

    Vedsegaard, Helle; Schrader, Anne-Marie; Rom, Gitte

    2016-01-01

    The current study responds to implementation challenges with translating evidence-based knowledge into practice. We explore how appreciative inquiry can be used in in-house learning sessions for nurses to enhance their knowledge in using a guideline on delirium as part of clinical decision making...... and axial coding drawing on the principles of grounded theory. The study shows that appreciative inquiry was meaningful to cardiology nurses in providing them with knowledge of using a guideline on delirium in clinical decision making, the main reasons being a) data on a current patient were included, b....... Through 18 sessions with 3–12 nurses, an appreciative inquiry approach was used. Specialist nurses from the Heart Centre of Copenhagen and senior lecturers from the Department of Nursing at Metropolitan University College facilitated the sessions. Field notes from the sessions were analysed using open...

  8. SANDS: an architecture for clinical decision support in a National Health Information Network.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2007-10-11

    A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

  9. [Cancer screening in clinical practice: the value of shared decision-making].

    Science.gov (United States)

    Cornuz, Jacques; Junod, Noëlle; Pasche, Olivier; Guessous, Idris

    2010-07-14

    Shared decision-making approach to uncertain clinical situations such as cancer screening seems more appropriate than ever. Shared decision making can be defined as an interactive process where physician and patient share all the stages of the decision making process. For patients who wish to be implicated in the management of their health conditions, physicians might express difficulty to do so. Use of patient decision aids appears to improve such process of shared decision making.

  10. Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice.

    Science.gov (United States)

    Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

    2010-05-01

    This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional community, and features of clinical practice such as private versus public practice as well as local management policies. This review brings together the different strands of knowledge concerning non-clinical influences on clinical decision-making. This aspect of decision-making may be the biggest obstacle to the reality of practising evidence-based medicine. It needs to be understood in order to develop clinical strategies that will facilitate the practice of evidence-based medicine.

  11. Non-clinical influences on clinical decision-making: a major challenge to evidence-based practice

    OpenAIRE

    Hajjaj, FM; Salek, MS; Basra, MKA; Finlay, AY

    2010-01-01

    This article reviews an aspect of daily clinical practice which is of critical importance in virtually every clinical consultation, but which is seldom formally considered. Non-clinical influences on clinical decision-making profoundly affect medical decisions. These influences include patient-related factors such as socioeconomic status, quality of life and patient's expectations and wishes, physician-related factors such as personal characteristics and interaction with their professional co...

  12. An application of multiattribute decision analysis to the Space Station Freedom program. Case study: Automation and robotics technology evaluation

    Science.gov (United States)

    Smith, Jeffrey H.; Levin, Richard R.; Carpenter, Elisabeth J.

    1990-01-01

    The results are described of an application of multiattribute analysis to the evaluation of high leverage prototyping technologies in the automation and robotics (A and R) areas that might contribute to the Space Station (SS) Freedom baseline design. An implication is that high leverage prototyping is beneficial to the SS Freedom Program as a means for transferring technology from the advanced development program to the baseline program. The process also highlights the tradeoffs to be made between subsidizing high value, low risk technology development versus high value, high risk technology developments. Twenty one A and R Technology tasks spanning a diverse array of technical concepts were evaluated using multiattribute decision analysis. Because of large uncertainties associated with characterizing the technologies, the methodology was modified to incorporate uncertainty. Eight attributes affected the rankings: initial cost, operation cost, crew productivity, safety, resource requirements, growth potential, and spinoff potential. The four attributes of initial cost, operations cost, crew productivity, and safety affected the rankings the most.

  13. Performance Evaluation of an Automated ELISA System for Alzheimer's Disease Detection in Clinical Routine.

    Science.gov (United States)

    Chiasserini, Davide; Biscetti, Leonardo; Farotti, Lucia; Eusebi, Paolo; Salvadori, Nicola; Lisetti, Viviana; Baschieri, Francesca; Chipi, Elena; Frattini, Giulia; Stoops, Erik; Vanderstichele, Hugo; Calabresi, Paolo; Parnetti, Lucilla

    2016-07-22

    The variability of Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers undermines their full-fledged introduction into routine diagnostics and clinical trials. Automation may help to increase precision and decrease operator errors, eventually improving the diagnostic performance. Here we evaluated three new CSF immunoassays, EUROIMMUNtrademark amyloid-β 1-40 (Aβ1-40), amyloid-β 1-42 (Aβ1-42), and total tau (t-tau), in combination with automated analysis of the samples. The CSF biomarkers were measured in a cohort consisting of AD patients (n = 28), mild cognitive impairment (MCI, n = 77), and neurological controls (OND, n = 35). MCI patients were evaluated yearly and cognitive functions were assessed by Mini-Mental State Examination. The patients clinically diagnosed with AD and MCI were classified according to the CSF biomarkers profile following NIA-AA criteria and the Erlangen score. Technical evaluation of the immunoassays was performed together with the calculation of their diagnostic performance. Furthermore, the results for EUROIMMUN Aβ1-42 and t-tau were compared to standard immunoassay methods (INNOTESTtrademark). EUROIMMUN assays for Aβ1-42 and t-tau correlated with INNOTEST (r = 0.83, p ratio measured with EUROIMMUN was the best parameter for AD detection and improved the diagnostic accuracy of Aβ1-42 (area under the curve = 0.93). In MCI patients, the Aβ1-42/Aβ1-40 ratio was associated with cognitive decline and clinical progression to AD.The diagnostic performance of the EUROIMMUN assays with automation is comparable to other currently used methods. The variability of the method and the value of the Aβ1-42/Aβ1-40 ratio in AD diagnosis need to be validated in large multi-center studies.

  14. Conventional Versus Automated Implantation of Loose Seeds in Prostate Brachytherapy: Analysis of Dosimetric and Clinical Results

    International Nuclear Information System (INIS)

    Genebes, Caroline; Filleron, Thomas; Graff, Pierre; Jonca, Frédéric; Huyghe, Eric; Thoulouzan, Matthieu; Soulie, Michel; Malavaud, Bernard; Aziza, Richard; Brun, Thomas; Delannes, Martine; Bachaud, Jean-Marc

    2013-01-01

    Purpose: To review the clinical outcome of I-125 permanent prostate brachytherapy (PPB) for low-risk and intermediate-risk prostate cancer and to compare 2 techniques of loose-seed implantation. Methods and Materials: 574 consecutive patients underwent I-125 PPB for low-risk and intermediate-risk prostate cancer between 2000 and 2008. Two successive techniques were used: conventional implantation from 2000 to 2004 and automated implantation (Nucletron, FIRST system) from 2004 to 2008. Dosimetric and biochemical recurrence-free (bNED) survival results were reported and compared for the 2 techniques. Univariate and multivariate analysis researched independent predictors for bNED survival. Results: 419 (73%) and 155 (27%) patients with low-risk and intermediate-risk disease, respectively, were treated (median follow-up time, 69.3 months). The 60-month bNED survival rates were 95.2% and 85.7%, respectively, for patients with low-risk and intermediate-risk disease (P=.04). In univariate analysis, patients treated with automated implantation had worse bNED survival rates than did those treated with conventional implantation (P<.0001). By day 30, patients treated with automated implantation showed lower values of dose delivered to 90% of prostate volume (D90) and volume of prostate receiving 100% of prescribed dose (V100). In multivariate analysis, implantation technique, Gleason score, and V100 on day 30 were independent predictors of recurrence-free status. Grade 3 urethritis and urinary incontinence were observed in 2.6% and 1.6% of the cohort, respectively, with no significant differences between the 2 techniques. No grade 3 proctitis was observed. Conclusion: Satisfactory 60-month bNED survival rates (93.1%) and acceptable toxicity (grade 3 urethritis <3%) were achieved by loose-seed implantation. Automated implantation was associated with worse dosimetric and bNED survival outcomes

  15. Conventional Versus Automated Implantation of Loose Seeds in Prostate Brachytherapy: Analysis of Dosimetric and Clinical Results

    Energy Technology Data Exchange (ETDEWEB)

    Genebes, Caroline, E-mail: genebes.caroline@claudiusregaud.fr [Radiation Oncology Department, Institut Claudius Regaud, Toulouse (France); Filleron, Thomas; Graff, Pierre [Radiation Oncology Department, Institut Claudius Regaud, Toulouse (France); Jonca, Frédéric [Department of Urology, Clinique Ambroise Paré, Toulouse (France); Huyghe, Eric; Thoulouzan, Matthieu; Soulie, Michel; Malavaud, Bernard [Department of Urology and Andrology, CHU Rangueil, Toulouse (France); Aziza, Richard; Brun, Thomas; Delannes, Martine; Bachaud, Jean-Marc [Radiation Oncology Department, Institut Claudius Regaud, Toulouse (France)

    2013-11-15

    Purpose: To review the clinical outcome of I-125 permanent prostate brachytherapy (PPB) for low-risk and intermediate-risk prostate cancer and to compare 2 techniques of loose-seed implantation. Methods and Materials: 574 consecutive patients underwent I-125 PPB for low-risk and intermediate-risk prostate cancer between 2000 and 2008. Two successive techniques were used: conventional implantation from 2000 to 2004 and automated implantation (Nucletron, FIRST system) from 2004 to 2008. Dosimetric and biochemical recurrence-free (bNED) survival results were reported and compared for the 2 techniques. Univariate and multivariate analysis researched independent predictors for bNED survival. Results: 419 (73%) and 155 (27%) patients with low-risk and intermediate-risk disease, respectively, were treated (median follow-up time, 69.3 months). The 60-month bNED survival rates were 95.2% and 85.7%, respectively, for patients with low-risk and intermediate-risk disease (P=.04). In univariate analysis, patients treated with automated implantation had worse bNED survival rates than did those treated with conventional implantation (P<.0001). By day 30, patients treated with automated implantation showed lower values of dose delivered to 90% of prostate volume (D90) and volume of prostate receiving 100% of prescribed dose (V100). In multivariate analysis, implantation technique, Gleason score, and V100 on day 30 were independent predictors of recurrence-free status. Grade 3 urethritis and urinary incontinence were observed in 2.6% and 1.6% of the cohort, respectively, with no significant differences between the 2 techniques. No grade 3 proctitis was observed. Conclusion: Satisfactory 60-month bNED survival rates (93.1%) and acceptable toxicity (grade 3 urethritis <3%) were achieved by loose-seed implantation. Automated implantation was associated with worse dosimetric and bNED survival outcomes.

  16. Vision 20/20: Automation and advanced computing in clinical radiation oncology

    International Nuclear Information System (INIS)

    Moore, Kevin L.; Moiseenko, Vitali; Kagadis, George C.; McNutt, Todd R.; Mutic, Sasa

    2014-01-01

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy

  17. Vision 20/20: Automation and advanced computing in clinical radiation oncology

    Energy Technology Data Exchange (ETDEWEB)

    Moore, Kevin L., E-mail: kevinmoore@ucsd.edu; Moiseenko, Vitali [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States); Kagadis, George C. [Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 26504 (Greece); McNutt, Todd R. [Department of Radiation Oncology and Molecular Radiation Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231 (United States); Mutic, Sasa [Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri 63110 (United States)

    2014-01-15

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

  18. Vision 20/20: Automation and advanced computing in clinical radiation oncology.

    Science.gov (United States)

    Moore, Kevin L; Kagadis, George C; McNutt, Todd R; Moiseenko, Vitali; Mutic, Sasa

    2014-01-01

    This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

  19. Pregnancy outcomes in Ghana : Relavance of clinical decision making support tools for frontline providers of care

    OpenAIRE

    Amoakoh-Coleman, M.

    2016-01-01

    Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy outcomes. Relevance of three clinical decision making support tools available to frontline providers of care in the Greater Accra region is discussed. These are routine maternal health service delivery data populati...

  20. Automated radiosynthesis of [{sup 11}C]morphine for clinical investigation

    Energy Technology Data Exchange (ETDEWEB)

    Fan Jinda [Department of Radiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States); Meissner, Konrad [Department of Anesthesiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States); Gaehle, Gregory G.; Li Shihong [Department of Radiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States); Kharasch, Evan D. [Department of Anesthesiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States); Mach, Robert H. [Department of Radiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States); Tu Zhude, E-mail: tuz@mir.wustl.ed [Department of Radiology, Washington University School of Medicine, 510 South Kingshighway Blvd. St. Louis, MO 63110 (United States)

    2011-02-15

    To meet a multiple-dose clinical evaluation of the P-gp modulation of [{sup 11}C]morphine delivery into the human brain, radiosynthesis of [{sup 11}C]morphine was accomplished on an automated system by N-methylation of normorphine with [{sup 11}C]CH{sub 3}I. A methodology employing optimized solid phase extraction of the HPLC eluent was developed. Radiosynthesis took 45 min with a radiochemical yield ranging from 45% to 50% and specific activity ranging from 20 to 26 Ci/{mu}mol (decay corrected to end-of-bombardment); radiochemical and chemical purities were >95% (n=28).

  1. NASA Wrangler: Automated Cloud-Based Data Assembly in the RECOVER Wildfire Decision Support System

    Science.gov (United States)

    Schnase, John; Carroll, Mark; Gill, Roger; Wooten, Margaret; Weber, Keith; Blair, Kindra; May, Jeffrey; Toombs, William

    2017-01-01

    NASA Wrangler is a loosely-coupled, event driven, highly parallel data aggregation service designed to take advantageof the elastic resource capabilities of cloud computing. Wrangler automatically collects Earth observational data, climate model outputs, derived remote sensing data products, and historic biophysical data for pre-, active-, and post-wildfire decision making. It is a core service of the RECOVER decision support system, which is providing rapid-response GIS analytic capabilities to state and local government agencies. Wrangler reduces to minutes the time needed to assemble and deliver crucial wildfire-related data.

  2. Clinical decision making in restorative dentistry, endodontics, and antibiotic prescription.

    Science.gov (United States)

    Zadik, Yehuda; Levin, Liran

    2008-01-01

    The purpose of this study was to evaluate the influence of geographic location of graduation (Israel, Eastern Europe, Latin America) on decision making regarding management of dental caries, periapical lesions, and antibiotic prescribing routines. A questionnaire was given to ninety-eight general practitioners regarding demographic and work habits. Photographs of lesions were shown on a screen. Participants reported recommended treatment and whether they would routinely prescribe antibiotics following regular endodontic treatment, retreatment, and impacted third molar surgical extraction in healthy patients. There was a 94 percent (n=92) response rate, of which eighty-five responses were used in the data analysis. Surgical treatment of asymptomatic enamel caries lesions was not recommended by most of the subjects, and surgery was recommended for DEJ caries lesions in low or moderate caries risk patients, both without significant differences between geographic regions of dental school graduation. Israelis had a lower frequency of retreatment in asymptomatic teeth that demonstrated periapical radiolucency with post restoration (without crown) compared to Latin Americans and East Europeans. Most of the participants would not retreat asymptomatic teeth that demonstrated periapical radiolucency with post and crown. After third molar surgery, 46 percent of participants routinely prescribed antibiotics. Significantly more Latin American graduates prescribed antibiotics following endodontic treatment, retreatment, and third molar extractions (pantibiotics) and overtreatment (caries) among young practitioners reflect failure of undergraduate education in proper use of antibiotics and management of the carious lesions according to the patient's clinical presentation and caries risk assessment rather than routinely undertaking surgical caries treatment.

  3. Factors and outcomes of decision making for cancer clinical trial participation.

    Science.gov (United States)

    Biedrzycki, Barbara A

    2011-09-01

    To describe factors and outcomes related to the decision-making process regarding participation in a cancer clinical trial. Cross-sectional, descriptive. Urban, academic, National Cancer Institute-designated comprehensive cancer center in the mid-Atlantic United States. 197 patients with advanced gastrointestinal cancer. Mailed survey using one investigator-developed instrument, eight instruments used in published research, and a medical record review. disease context, sociodemographics, hope, quality of life, trust in healthcare system, trust in health professional, preference for research decision control, understanding risks, and information. decision to accept or decline research participation and satisfaction with this decision. All of the factors within the Research Decision Making Model together predicted cancer clinical trial participation and satisfaction with this decision. The most frequently preferred decision-making style for research participation was shared (collaborative) (83%). Multiple factors affect decision making for cancer clinical trial participation and satisfaction with this decision. Shared decision making previously was an unrecognized factor and requires further investigation. Enhancing the process of research decision making may facilitate an increase in cancer clinical trial enrollment rates. Oncology nurses have unique opportunities as educators and researchers to support shared decision making by those who prefer this method for deciding whether to accept or decline cancer clinical trial participation.

  4. THE ASSOCIATION BETWEEN OFFICE AUTOMATION AND IMPROVEMENT OF DECISION-MAKING AND PRODUCTIVITY OF EMPLOYEES OF YOUTH AND SPORT OFFICES OF WEST AZERBAIJAN PROVINCE, IRAN

    OpenAIRE

    Mostafa Mostafa pour; Ali Amini; Vadoud Shoshtary; Auoub Izadi; Yousef Esmayilian; Fatemeh Salami; Bager Khakpour

    2017-01-01

    The availability of precise, relevant, timely and new information increases the speed and precision of decision making. The objective of present study is to examine the association between office automation, improvement of decision-making and productivity of employees of Youth and Sport offices of West Azerbaijan Province. The statistical population of present study consists of 130 employees of Youth and Sport offices of West Azerbaijan Province selected through simple random sampling. The st...

  5. Acceptance of clinical decision support surveillance technology in the clinical pharmacy.

    Science.gov (United States)

    English, Dan; Ankem, Kalyani; English, Kathleen

    2017-03-01

    There are clinical and economic benefits to incorporating clinical decision support systems (CDSSs) in patient care interventions in the clinical pharmacy setting. However, user dissatisfaction and resistance to HIT can prevent optimal use of such systems, particularly when users employ system workarounds and overrides. The present study applied a modified version of the unified theory of acceptance and use of technology (UTAUT) to evaluate the disposition and satisfaction with CDSS among clinical pharmacists who perform surveillance to identify potential medication therapy interventions on patients in the hospital setting. A survey of clinical pharmacists (N = 48) was conducted. Partial least squares (PLS) regression was used to analyze the influence of the UTAUT-related variables on behavioral intention and satisfaction with CDSS among clinical pharmacists. While behavioral intention did not predict actual use of HIT, facilitating conditions had a direct effect on pharmacists' use of CDSS. Likewise, satisfaction with CDSS was found to have a direct effect on use, with more satisfied users being less inclined to employ workarounds or overrides of the system. Based on the findings, organizational structures that facilitate CDSS use and user satisfaction affect the extent to which pharmacy and health care management maximize use in the clinical pharmacy setting.

  6. Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

    Science.gov (United States)

    Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

    2009-04-01

    Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

  7. Forms of Knowledge Incorporated in Clinical Decision-making among Newly-Graduated Nurses: A Metasynthesis

    DEFF Research Database (Denmark)

    Voldbjerg, Siri; Elgaard Sørensen, Erik; Grønkjær, Mette

    2014-01-01

    Clinical-decision-making is of decisive importance to how evidence-based practice is put into practice. Schools of Nursing have a responsibility to teach and train nursing students to make clinical decisions within a frame of evidence-based practice. Clinical decision-making among nurses has been...... explored from numerous angles using a diversity of methodologies. Existing research has mainly focused on promoting and inhibiting factors for implementation of evidence-based practice and incorporation of research evidence in the clinical-decision. Little attention has been given to the nurses' behavior......, including the knowledge that actually informs the newly graduated nurses’ clinical decision. The aim of the study is to combine and synthesize results from qualitative research. Noblit and Hare’s meta-ethnographic approach is used to conduct a metasynthesis of qualitative research that has studied...

  8. Automated Proton Track Identification in MicroBooNE Using Gradient Boosted Decision Trees

    Energy Technology Data Exchange (ETDEWEB)

    Woodruff, Katherine [New Mexico State U.

    2017-10-02

    MicroBooNE is a liquid argon time projection chamber (LArTPC) neutrino experiment that is currently running in the Booster Neutrino Beam at Fermilab. LArTPC technology allows for high-resolution, three-dimensional representations of neutrino interactions. A wide variety of software tools for automated reconstruction and selection of particle tracks in LArTPCs are actively being developed. Short, isolated proton tracks, the signal for low- momentum-transfer neutral current (NC) elastic events, are easily hidden in a large cosmic background. Detecting these low-energy tracks will allow us to probe interesting regions of the proton's spin structure. An effective method for selecting NC elastic events is to combine a highly efficient track reconstruction algorithm to find all candidate tracks with highly accurate particle identification using a machine learning algorithm. We present our work on particle track classification using gradient tree boosting software (XGBoost) and the performance on simulated neutrino data.

  9. Encounter Decision Aid vs. Clinical Decision Support or Usual Care to Support Patient-Centered Treatment Decisions in Osteoporosis: The Osteoporosis Choice Randomized Trial II.

    Directory of Open Access Journals (Sweden)

    Annie LeBlanc

    Full Text Available Osteoporosis Choice, an encounter decision aid, can engage patients and clinicians in shared decision making about osteoporosis treatment. Its effectiveness compared to the routine provision to clinicians of the patient's estimated risk of fracture using the FRAX calculator is unknown.Patient-level, randomized, three-arm trial enrolling women over 50 with osteopenia or osteoporosis eligible for treatment with bisphosphonates, where the use of Osteoporosis Choice was compared to FRAX only and to usual care to determine impact on patient knowledge, decisional conflict, involvement in the decision-making process, decision to start and adherence to bisphosphonates.We enrolled 79 women in the three arms. Because FRAX estimation alone and usual care produced similar results, we grouped them for analysis. Compared to these, use of Osteoporosis Choice increased patient knowledge (median score 6 vs. 4, p = .01, improved understanding of fracture risk and risk reduction with bisphosphonates (p = .01 and p<.0001, respectively, had no effect on decision conflict, and increased patient engagement in the decision making process (OPTION scores 57% vs. 43%, p = .001. Encounters with the decision aid were 0.8 minutes longer (range: 33 minutes shorter to 3.0 minutes longer. There were twice as many patients receiving and filling prescriptions in the decision aid arm (83% vs. 40%, p = .07; medication adherence at 6 months was no different across arms.Supporting both patients and clinicians during the clinical encounter with the Osteoporosis Choice decision aid efficiently improves treatment decision making when compared to usual care with or without clinical decision support with FRAX results.clinical trials.gov NCT00949611.

  10. Patients' perceptions of sharing in decisions: a systematic review of interventions to enhance shared decision making in routine clinical practice.

    Science.gov (United States)

    Légaré, France; Turcotte, Stéphane; Stacey, Dawn; Ratté, Stéphane; Kryworuchko, Jennifer; Graham, Ian D

    2012-01-01

    Shared decision making is the process in which a healthcare choice is made jointly by the health professional and the patient. Little is known about what patients view as effective or ineffective strategies to implement shared decision making in routine clinical practice. This systematic review evaluates the effectiveness of interventions to improve health professionals' adoption of shared decision making in routine clinical practice, as seen by patients. We searched electronic databases (PubMed, the Cochrane Library, EMBASE, CINAHL, and PsycINFO) from their inception to mid-March 2009. We found additional material by reviewing the reference lists of the studies found in the databases; systematic reviews of studies on shared decision making; the proceedings of various editions of the International Shared Decision Making Conference; and the transcripts of the Society for Medical Decision Making's meetings. In our study selection, we included randomized controlled trials, controlled clinical trials, controlled before-and-after studies, and interrupted time series analyses in which patients evaluated interventions to improve health professionals' adoption of shared decision making. The interventions in question consisted of the distribution of printed educational material; educational meetings; audit and feedback; reminders; and patient-mediated initiatives (e.g. patient decision aids). Two reviewers independently screened the studies and extracted data. Statistical analyses considered categorical and continuous process measures. We computed the standardized effect size for each outcome at the 95% confidence interval. The primary outcome of interest was health professionals' adoption of shared decision making as reported by patients in a self-administered questionnaire. Of the 6764 search results, 21 studies reported 35 relevant comparisons. Overall, the quality of the studies ranged from 0% to 83%. Only three of the 21 studies reported a clinically significant effect

  11. The impact of automation on organizational changes in a community hospital clinical microbiology laboratory.

    Science.gov (United States)

    Camporese, Alessandro

    2004-06-01

    The diagnosis of infectious diseases and the role of the microbiology laboratory are currently undergoing a process of change. The need for overall efficiency in providing results is now given the same importance as accuracy. This means that laboratories must be able to produce quality results in less time with the capacity to interpret the results clinically. To improve the clinical impact of microbiology results, the new challenge facing the microbiologist has become one of process management instead of pure analysis. A proper project management process designed to improve workflow, reduce analytical time, and provide the same high quality results without losing valuable time treating the patient, has become essential. Our objective was to study the impact of introducing automation and computerization into the microbiology laboratory, and the reorganization of the laboratory workflow, i.e. scheduling personnel to work shifts covering both the entire day and the entire week. In our laboratory, the introduction of automation and computerization, as well as the reorganization of personnel, thus the workflow itself, has resulted in an improvement in response time and greater efficiency in diagnostic procedures.

  12. Integration of Automated Decision Support Systems with Data Mining Abstract: A Client Perspective

    OpenAIRE

    Abdullah Saad AL-Malaise

    2013-01-01

    Customer’s behavior and satisfaction are always play important role to increase organization’s growth and market value. Customers are on top priority for the growing organization to build up their businesses. In this paper presents the architecture of Decision Support Systems (DSS) in connection to deal with the customer’s enquiries and requests. Main purpose behind the proposed model is to enhance the customer’s satisfaction and behavior using DSS. We proposed model by extension in tradition...

  13. RECOVER: An Automated, Cloud-Based Decision Support System for Post-Fire Rehabilitation Planning

    Science.gov (United States)

    Schnase, J. L.; Carroll, M. L.; Weber, K. T.; Brown, M. E.; Gill, R. L.; Wooten, M.; May, J.; Serr, K.; Smith, E.; Goldsby, R.; Newtoff, K.; Bradford, K.; Doyle, C.; Volker, E.; Weber, S.

    2014-11-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

  14. RECOVER: An Automated Cloud-Based Decision Support System for Post-fire Rehabilitation Planning

    Science.gov (United States)

    Schnase, John L.; Carroll, Mark; Weber, K. T.; Brown, Molly E.; Gill, Roger L.; Wooten, Margaret; May J.; Serr, K.; Smith, E.; Goldsby, R.; hide

    2014-01-01

    RECOVER is a site-specific decision support system that automatically brings together in a single analysis environment the information necessary for post-fire rehabilitation decision-making. After a major wildfire, law requires that the federal land management agencies certify a comprehensive plan for public safety, burned area stabilization, resource protection, and site recovery. These burned area emergency response (BAER) plans are a crucial part of our national response to wildfire disasters and depend heavily on data acquired from a variety of sources. Final plans are due within 21 days of control of a major wildfire and become the guiding document for managing the activities and budgets for all subsequent remediation efforts. There are few instances in the federal government where plans of such wide-ranging scope and importance are assembled on such short notice and translated into action more quickly. RECOVER has been designed in close collaboration with our agency partners and directly addresses their high-priority decision-making requirements. In response to a fire detection event, RECOVER uses the rapid resource allocation capabilities of cloud computing to automatically collect Earth observational data, derived decision products, and historic biophysical data so that when the fire is contained, BAER teams will have a complete and ready-to-use RECOVER dataset and GIS analysis environment customized for the target wildfire. Initial studies suggest that RECOVER can transform this information-intensive process by reducing from days to a matter of minutes the time required to assemble and deliver crucial wildfire-related data.

  15. Clinical decision making in a high-risk primary care environment: a qualitative study in the UK.

    Science.gov (United States)

    Balla, John; Heneghan, Carl; Thompson, Matthew; Balla, Margaret

    2012-01-01

    Examine clinical reasoning and decision making in an out of hours (OOH) primary care setting to gain insights into how general practitioners (GPs) make clinical decisions and manage risk in this environment. Semi-structured interviews using open-ended questions. A 2-month qualitative interview study conducted in Oxfordshire, UK. 21 GPs working in OOH primary care. The most powerful themes to emerge related to dealing with urgent potentially high-risk cases, keeping patients safe and responding to their needs, while trying to keep patients out of hospital and the concept of 'fire fighting'. There were a number of well-defined characteristics that GPs reported making presentations easy or difficult to deal with. Severely ill patients were straightforward, while the older people, with complex multisystem diseases, were often difficult. GPs stopped collecting clinical information and came to clinical decisions when high-risk disease and severe illness requiring hospital attention has been excluded; they had responded directly to the patient's needs and there was a reliable safety net in place. Learning points that GPs identified as important for trainees in the OOH setting included the importance of developing rapport in spite of time pressures, learning to deal with uncertainty and learning about common presentations with a focus on critical cues to exclude severe illness. The findings support suggestions that improvements in primary care OOH could be achieved by including automated and regular timely feedback system for GPs and individual peer and expert clinician support for GPs with regular meetings to discuss recent cases. In addition, trainee support and mentoring to focus on clinical skills, knowledge and risk management issues specific to OOH is currently required. Investigating the stopping rules used for diagnostic closure may provide new insights into the root causes of clinical error in such a high-risk setting.

  16. Parametric vs. Nonparametric Regression Modelling within Clinical Decision Support

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan; Zvárová, Jana

    2017-01-01

    Roč. 5, č. 1 (2017), s. 21-27 ISSN 1805-8698 R&D Projects: GA ČR GA17-01251S Institutional support: RVO:67985807 Keywords : decision support systems * decision rules * statistical analysis * nonparametric regression Subject RIV: IN - Informatics, Computer Science OBOR OECD: Statistics and probability

  17. Automating Construction of Machine Learning Models With Clinical Big Data: Proposal Rationale and Methods.

    Science.gov (United States)

    Luo, Gang; Stone, Bryan L; Johnson, Michael D; Tarczy-Hornoch, Peter; Wilcox, Adam B; Mooney, Sean D; Sheng, Xiaoming; Haug, Peter J; Nkoy, Flory L

    2017-08-29

    To improve health outcomes and cut health care costs, we often need to conduct prediction/classification using large clinical datasets (aka, clinical big data), for example, to identify high-risk patients for preventive interventions. Machine learning has been proposed as a key technology for doing this. Machine learning has won most data science competitions and could support many clinical activities, yet only 15% of hospitals use it for even limited purposes. Despite familiarity with data, health care researchers often lack machine learning expertise to directly use clinical big data, creating a hurdle in realizing value from their data. Health care researchers can work with data scientists with deep machine learning knowledge, but it takes time and effort for both parties to communicate effectively. Facing a shortage in the United States of data scientists and hiring competition from companies with deep pockets, health care systems have difficulty recruiting data scientists. Building and generalizing a machine learning model often requires hundreds to thousands of manual iterations by data scientists to select the following: (1) hyper-parameter values and complex algorithms that greatly affect model accuracy and (2) operators and periods for temporally aggregating clinical attributes (eg, whether a patient's weight kept rising in the past year). This process becomes infeasible with limited budgets. This study's goal is to enable health care researchers to directly use clinical big data, make machine learning feasible with limited budgets and data scientist resources, and realize value from data. This study will allow us to achieve the following: (1) finish developing the new software, Automated Machine Learning (Auto-ML), to automate model selection for machine learning with clinical big data and validate Auto-ML on seven benchmark modeling problems of clinical importance; (2) apply Auto-ML and novel methodology to two new modeling problems crucial for care

  18. Automated Manufacturing of Potent CD20-Directed Chimeric Antigen Receptor T Cells for Clinical Use.

    Science.gov (United States)

    Lock, Dominik; Mockel-Tenbrinck, Nadine; Drechsel, Katharina; Barth, Carola; Mauer, Daniela; Schaser, Thomas; Kolbe, Carolin; Al Rawashdeh, Wael; Brauner, Janina; Hardt, Olaf; Pflug, Natali; Holtick, Udo; Borchmann, Peter; Assenmacher, Mario; Kaiser, Andrew

    2017-10-01

    The clinical success of gene-engineered T cells expressing a chimeric antigen receptor (CAR), as manifested in several clinical trials for the treatment of B cell malignancies, warrants the development of a simple and robust manufacturing procedure capable of reducing to a minimum the challenges associated with its complexity. Conventional protocols comprise many open handling steps, are labor intensive, and are difficult to upscale for large numbers of patients. Furthermore, extensive training of personnel is required to avoid operator variations. An automated current Good Manufacturing Practice-compliant process has therefore been developed for the generation of gene-engineered T cells. Upon installation of the closed, single-use tubing set on the CliniMACS Prodigy™, sterile welding of the starting cell product, and sterile connection of the required reagents, T cells are magnetically enriched, stimulated, transduced using lentiviral vectors, expanded, and formulated. Starting from healthy donor (HD) or lymphoma or melanoma patient material (PM), the robustness and reproducibility of the manufacturing of anti-CD20 specific CAR T cells were verified. Independent of the starting material, operator, or device, the process consistently yielded a therapeutic dose of highly viable CAR T cells. Interestingly, the formulated product obtained with PM was comparable to that of HD with respect to cell composition, phenotype, and function, even though the starting material differed significantly. Potent antitumor reactivity of the produced anti-CD20 CAR T cells was shown in vitro as well as in vivo. In summary, the automated T cell transduction process meets the requirements for clinical manufacturing that the authors intend to use in two separate clinical trials for the treatment of melanoma and B cell lymphoma.

  19. Decision Making in the PICU: An Examination of Factors Influencing Participation Decisions in Phase III Randomized Clinical Trials

    Science.gov (United States)

    Slosky, Laura E.; Burke, Natasha L.; Siminoff, Laura A.

    2014-01-01

    Background. In stressful situations, decision making processes related to informed consent may be compromised. Given the profound levels of distress that surrogates of children in pediatric intensive care units (PICU) experience, it is important to understand what factors may be influencing the decision making process beyond the informed consent. The purpose of this study was to evaluate the role of clinician influence and other factors on decision making regarding participation in a randomized clinical trial (RCT). Method. Participants were 76 children under sedation in a PICU and their surrogate decision makers. Measures included the Post Decision Clinician Survey, observer checklist, and post-decision interview. Results. Age of the pediatric patient was related to participation decisions in the RCT such that older children were more likely to be enrolled. Mentioning the sponsoring institution was associated with declining to participate in the RCT. Type of health care provider and overt recommendations to participate were not related to enrollment. Conclusion. Decisions to participate in research by surrogates of children in the PICU appear to relate to child demographics and subtleties in communication; however, no modifiable characteristics were related to increased participation, indicating that the informed consent process may not be compromised in this population. PMID:25161672

  20. Pregnancy outcomes in Ghana : Relavance of clinical decision making support tools for frontline providers of care

    NARCIS (Netherlands)

    Amoakoh-Coleman, M.

    2016-01-01

    Ghana’s slow progress towards attaining millennium development goal 5 has been associated with gaps in quality of care, particularly quality of clinical decision making for clients. This thesis reviews the relevance and effect of clinical decision making support tools on pregnancy

  1. Clinical Decision Support to Implement CYP2D6 Drug-Gene Interaction.

    Science.gov (United States)

    Caraballo, Pedro J; Parkulo, Mark; Blair, David; Elliott, Michelle; Schultz, Cloann; Sutton, Joseph; Rao, Padma; Bruflat, Jamie; Bleimeyer, Robert; Crooks, John; Gabrielson, Donald; Nicholson, Wayne; Rohrer Vitek, Carolyn; Wix, Kelly; Bielinski, Suzette J; Pathak, Jyotishman; Kullo, Iftikhar

    2015-01-01

    The level of CYP2D6 metabolic activity can be predicted by pharmacogenomic testing, and concomitant use of clinical decision support has the potential to prevent adverse effects from those drugs metabolized by this enzyme. Our initial findings after implementation of clinical decision support alerts integrated in the electronic health records suggest high feasibility, but also identify important challenges.

  2. Clinical decision making and mental health service use in people with severe mental illness across Europe

    OpenAIRE

    Cosh, S.; Zentner, N.; Ay, E.; Loos, S.; Slade, Mike; Maj, Mario; Salzano, A.; Berecz, R.; Glaub, T.; Munk-Jørgensen, Povl; Krogsgaard Bording, M.; Rössler, Wulf; Kawohl, Wolfram; Puschner, Bernd

    2017-01-01

    Objective: This study aims to explore relationships between preferred and experienced clinical decision making with service use, and associated costs, by people with severe mental illness.\\ud Methods: Prospective observational study of mental healthcare in six European countries: Germany, UK, Italy Hungary, Denmark and Switzerland. Patients (N = 588) and treating clinicians (N = 213) reported preferred and experienced decision making at baseline using the Clinical Decision Making Style Scale ...

  3. Factors influencing the clinical decision-making of midwives: a qualitative study.

    Science.gov (United States)

    Daemers, Darie O A; van Limbeek, Evelien B M; Wijnen, Hennie A A; Nieuwenhuijze, Marianne J; de Vries, Raymond G

    2017-10-06

    Although midwives make clinical decisions that have an impact on the health and well-being of mothers and babies, little is known about how they make those decisions. Wide variation in intrapartum decisions to refer women to obstetrician-led care suggests that midwives' decisions are based on more than the evidence based medicine (EBM) model - i.e. clinical evidence, midwife's expertise, and woman's values - alone. With this study we aimed to explore the factors that influence clinical decision-making of midwives who work independently. We used a qualitative approach, conducting in-depth interviews with a purposive sample of 11 Dutch primary care midwives. Data collection took place between May and September 2015. The interviews were semi-structured, using written vignettes to solicit midwives' clinical decision-making processes (Think Aloud method). We performed thematic analysis on the transcripts. We identified five themes that influenced clinical decision-making: the pregnant woman as a whole person, sources of knowledge, the midwife as a whole person, the collaboration between maternity care professionals, and the organisation of care. Regarding the midwife, her decisions were shaped not only by her experience, intuition, and personal circumstances, but also by her attitudes about physiology, woman-centredness, shared decision-making, and collaboration with other professionals. The nature of the local collaboration between maternity care professionals and locally-developed protocols dominated midwives' clinical decision-making. When midwives and obstetricians had different philosophies of care and different practice styles, their collaborative efforts were challenged. Midwives' clinical decision-making is a more varied and complex process than the EBM framework suggests. If midwives are to succeed in their role as promoters and protectors of physiological pregnancy and birth, they need to understand how clinical decisions in a multidisciplinary context are

  4. Enhancing clinical decision making: development of a contiguous definition and conceptual framework.

    Science.gov (United States)

    Tiffen, Jennifer; Corbridge, Susan J; Slimmer, Lynda

    2014-01-01

    Clinical decision making is a term frequently used to describe the fundamental role of the nurse practitioner; however, other terms have been used interchangeably. The purpose of this article is to begin the process of developing a definition and framework of clinical decision making. The developed definition was "Clinical decision making is a contextual, continuous, and evolving process, where data are gathered, interpreted, and evaluated in order to select an evidence-based choice of action." A contiguous framework for clinical decision making specific for nurse practitioners is also proposed. Having a clear and unique understanding of clinical decision making will allow for consistent use of the term, which is relevant given the changing educational requirements for nurse practitioners and broadening scope of practice. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. Automated technical validation--a real time expert system for decision support.

    Science.gov (United States)

    de Graeve, J S; Cambus, J P; Gruson, A; Valdiguié, P M

    1996-04-15

    Dealing daily with various machines and various control specimens provides a lot of data that cannot be processed manually. In order to help decision-making we wrote specific software coping with the traditional QC, with patient data (mean of normals, delta check) and with criteria related to the analytical equipment (flags and alarms). Four machines (3 Ektachem 700 and 1 Hitachi 911) analysing 25 common chemical tests are controlled. Every day, three different control specimens and one more once a week (regional survey) are run on the various pieces of equipment. The data are collected on a 486 microcomputer connected to the central computer. For every parameter the standard deviation is compared with the published acceptable limits and the Westgard's rules are computed. The mean of normals is continuously monitored. The final decision induces either an alarm sound and the print-out of the cause of rejection or, if no alarms happen, the daily print-out of recorded data, with or without the Levey Jennings graphs.

  6. SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

    Science.gov (United States)

    Wright, Adam; Sittig, Dean F

    2008-12-01

    In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

  7. A controlled trial of automated classification of negation from clinical notes

    Directory of Open Access Journals (Sweden)

    Carruth William

    2005-05-01

    Full Text Available Abstract Background Identification of negation in electronic health records is essential if we are to understand the computable meaning of the records: Our objective is to compare the accuracy of an automated mechanism for assignment of Negation to clinical concepts within a compositional expression with Human Assigned Negation. Also to perform a failure analysis to identify the causes of poorly identified negation (i.e. Missed Conceptual Representation, Inaccurate Conceptual Representation, Missed Negation, Inaccurate identification of Negation. Methods 41 Clinical Documents (Medical Evaluations; sometimes outside of Mayo these are referred to as History and Physical Examinations were parsed using the Mayo Vocabulary Server Parsing Engine. SNOMED-CT™ was used to provide concept coverage for the clinical concepts in the record. These records resulted in identification of Concepts and textual clues to Negation. These records were reviewed by an independent medical terminologist, and the results were tallied in a spreadsheet. Where questions on the review arose Internal Medicine Faculty were employed to make a final determination. Results SNOMED-CT was used to provide concept coverage of the 14,792 Concepts in 41 Health Records from John's Hopkins University. Of these, 1,823 Concepts were identified as negative by Human review. The sensitivity (Recall of the assignment of negation was 97.2% (p Conclusion Automated assignment of negation to concepts identified in health records based on review of the text is feasible and practical. Lexical assignment of negation is a good test of true Negativity as judged by the high sensitivity, specificity and positive likelihood ratio of the test. SNOMED-CT had overall coverage of 88.7% of the concepts being negated.

  8. When to trust our learners? Clinical teachers' perceptions of decision variables in the entrustment process.

    Science.gov (United States)

    Duijn, Chantal C M A; Welink, Lisanne S; Bok, Harold G J; Ten Cate, Olle T J

    2018-06-01

    Clinical training programs increasingly use entrustable professional activities (EPAs) as focus of assessment. However, questions remain about which information should ground decisions to trust learners. This qualitative study aimed to identify decision variables in the workplace that clinical teachers find relevant in the elaboration of the entrustment decision processes. The findings can substantiate entrustment decision-making in the clinical workplace. Focus groups were conducted with medical and veterinary clinical teachers, using the structured consensus method of the Nominal Group Technique to generate decision variables. A ranking was made based on a relevance score assigned by the clinical teachers to the different decision variables. Field notes, audio recordings and flip chart lists were analyzed and subsequently translated and, as a form of axial coding, merged into one list, combining the decision variables that were similar in their meaning. A list of 11 and 17 decision variables were acknowledged as relevant by the medical and veterinary teacher groups, respectively. The focus groups yielded 21 unique decision variables that were considered relevant to inform readiness to perform a clinical task on a designated level of supervision. The decision variables consisted of skills, generic qualities, characteristics, previous performance or other information. We were able to group the decision variables into five categories: ability, humility, integrity, reliability and adequate exposure. To entrust a learner to perform a task at a specific level of supervision, a supervisor needs information to support such a judgement. This trust cannot be credited on a single case at a single moment of assessment, but requires different variables and multiple sources of information. This study provides an overview of decision variables giving evidence to justify the multifactorial process of making an entrustment decision.

  9. A Representation for Gaining Insight into Clinical Decision Models

    Science.gov (United States)

    Jimison, Holly B.

    1988-01-01

    For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient- specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

  10. Quantifying explainable discrimination and removing illegal discrimination in automated decision making

    KAUST Repository

    Kamiran, Faisal

    2012-11-18

    Recently, the following discrimination-aware classification problem was introduced. Historical data used for supervised learning may contain discrimination, for instance, with respect to gender. The question addressed by discrimination-aware techniques is, given sensitive attribute, how to train discrimination-free classifiers on such historical data that are discriminative, with respect to the given sensitive attribute. Existing techniques that deal with this problem aim at removing all discrimination and do not take into account that part of the discrimination may be explainable by other attributes. For example, in a job application, the education level of a job candidate could be such an explainable attribute. If the data contain many highly educated male candidates and only few highly educated women, a difference in acceptance rates between woman and man does not necessarily reflect gender discrimination, as it could be explained by the different levels of education. Even though selecting on education level would result in more males being accepted, a difference with respect to such a criterion would not be considered to be undesirable, nor illegal. Current state-of-the-art techniques, however, do not take such gender-neutral explanations into account and tend to overreact and actually start reverse discriminating, as we will show in this paper. Therefore, we introduce and analyze the refined notion of conditional non-discrimination in classifier design. We show that some of the differences in decisions across the sensitive groups can be explainable and are hence tolerable. Therefore, we develop methodology for quantifying the explainable discrimination and algorithmic techniques for removing the illegal discrimination when one or more attributes are considered as explanatory. Experimental evaluation on synthetic and real-world classification datasets demonstrates that the new techniques are superior to the old ones in this new context, as they succeed in

  11. Clinical trial or standard treatment? Shared decision making at the department of oncology

    DEFF Research Database (Denmark)

    Gregersen, Trine Ammentorp; Birkelund, Regner; Ammentorp, Jette

    2016-01-01

    Title: Clinical trial or standard treatment? Shared decision making at the department of oncology. Authors: Ph.d. student, Trine A. Gregersen. Trine.gregersen@rsyd.dk. Department of Oncology. Health Services Research Unit Lillebaelt Hospital / IRS University of Southern Denmark. Professor, Regner...... are involved in difficult treatment decisions including participation in clinical trials. The literature indicates that the decision is very often based on little knowledge about the treatment and that many patients who have consented to participate in a clinical trial are not always aware...... that they are participating in a trial. This place great demand on the healthcare providers’ ability to involve and advise patients in the decisions. The aim of this study is to investigate the characteristics of the communication when decisions about participation in clinical oncology trial are made and the patients...

  12. Clinical decision making of experienced and novice nurses.

    Science.gov (United States)

    Tabak, N; Bar-Tal, Y; Cohen-Mansfield, J

    1996-10-01

    Decision making is an important daily nursing activity. Given contradictory past findings concerning the ease of use cognitive schema for reaching decisions among experts and novices, we chose to examine consistency of information as a parameter that may clarify the process of decision making. Ninety-two experienced nurses and 65 nursing students rated their decisional difficulty and levels of certainty in reaching a diagnosis for two scenarios: one including consistent information and one providing information that was partly inconsistent with the given diagnosis. For the consistent information, students showed more difficulty and less certainty in the given diagnosis than the experienced nurses. The inconsistent scenario was perceived as more difficult by nurses in comparison to students. The cognitive processes responsible for these results are discussed.

  13. Clinical decision making in dermatology: observation of consultations and the patients' perspectives.

    Science.gov (United States)

    Hajjaj, F M; Salek, M S; Basra, M K A; Finlay, A Y

    2010-01-01

    Clinical decision making is a complex process and might be influenced by a wide range of clinical and non-clinical factors. Little is known about this process in dermatology. The aim of this study was to explore the different types of management decisions made in dermatology and to identify factors influencing those decisions from observation of consultations and interviews with the patients. 61 patient consultations were observed by a physician with experience in dermatology. The patients were interviewed immediately after each consultation. Consultations and interviews were audio recorded, transcribed and their content analysed using thematic content analysis. The most common management decisions made during the consultations included: follow-up, carrying out laboratory investigation, starting new topical treatment, renewal of systemic treatment, renewal of topical treatment, discharging patients and starting new systemic treatment. Common influences on those decisions included: clinical factors such as ineffectiveness of previous therapy, adherence to prescribing guidelines, side-effects of medications, previous experience with the treatment, deterioration or improvement in the skin condition, and chronicity of skin condition. Non-clinical factors included: patient's quality of life, patient's friends or relatives, patient's time commitment, travel or transportation difficulties, treatment-related costs, availability of consultant, and availability of treatment. The study has shown that patients are aware that management decisions in dermatology are influenced by a wide range of clinical and non-clinical factors. Education programmes should be developed to improve the quality of decision making. Copyright © 2010 S. Karger AG, Basel.

  14. Complacency and Automation Bias in the Use of Imperfect Automation.

    Science.gov (United States)

    Wickens, Christopher D; Clegg, Benjamin A; Vieane, Alex Z; Sebok, Angelia L

    2015-08-01

    We examine the effects of two different kinds of decision-aiding automation errors on human-automation interaction (HAI), occurring at the first failure following repeated exposure to correctly functioning automation. The two errors are incorrect advice, triggering the automation bias, and missing advice, reflecting complacency. Contrasts between analogous automation errors in alerting systems, rather than decision aiding, have revealed that alerting false alarms are more problematic to HAI than alerting misses are. Prior research in decision aiding, although contrasting the two aiding errors (incorrect vs. missing), has confounded error expectancy. Participants performed an environmental process control simulation with and without decision aiding. For those with the aid, automation dependence was created through several trials of perfect aiding performance, and an unexpected automation error was then imposed in which automation was either gone (one group) or wrong (a second group). A control group received no automation support. The correct aid supported faster and more accurate diagnosis and lower workload. The aid failure degraded all three variables, but "automation wrong" had a much greater effect on accuracy, reflecting the automation bias, than did "automation gone," reflecting the impact of complacency. Some complacency was manifested for automation gone, by a longer latency and more modest reduction in accuracy. Automation wrong, creating the automation bias, appears to be a more problematic form of automation error than automation gone, reflecting complacency. Decision-aiding automation should indicate its lower degree of confidence in uncertain environments to avoid the automation bias. © 2015, Human Factors and Ergonomics Society.

  15. Clinical evaluation of 64-slice CT assessment of global left ventricular function using automated cardiac phase selection

    International Nuclear Information System (INIS)

    Joemai, Raoul M.S.; Geleijns, Joemai; Veldkamp, Wouter J.H.; Kroft, Lucia J.M.

    2008-01-01

    Left ventricular (LV) function provides prognostic information regarding the morbidity and mortality of patients. An automated cardiac phase selection algorithm has the potential to support the assessment of LV function with computed tomography (CT). This algorithm is clinically evaluated for 64-slice cardiac CT. Examinations of twenty consecutive patients were selected. Electrocardiogram gated contrast-enhanced CT was performed. Reconstructions were performed using an automated and a manual method, followed by the determination of the global LV function. Significances were tested using 2-sided Student's t-tests. Reduction in post processing time and storage capacity were estimated. A slightly smaller mean end-systolic volume was found with the automated method (52±18 ml vs 54±17 ml, p=0.02, r=0.99). The mean LV ejection fraction was slightly larger with the automated method (65±8% vs 64±8%, p=0.004, r=0.99). The estimated reduction in post processing time was maximal 5 min per patient with a potential 80% data storage reduction. Results of the automated phase selection algorithm are similar to the manual method. The automated tool reduces post processing time, reconstruction time and transfer time. (author)

  16. Mental Workload as a Key Factor in Clinical Decision Making

    Science.gov (United States)

    Byrne, Aidan

    2013-01-01

    The decision making process is central to the practice of a clinician and has traditionally been described in terms of the hypothetico-deductive model. More recently, models adapted from cognitive psychology, such as the dual process and script theories have proved useful in explaining patterns of practice not consistent with purely cognitive…

  17. Barriers and opportunities for shared decision making in clinical practice

    NARCIS (Netherlands)

    Schuitmaker-Warnaar, T.J.; Scheele, Fedde

    2017-01-01

    Shared decision-making (SDM) is promoted as tool for improving quality and responsiveness of care, while lowering overall costs. The underlying idea of SDM is well-conceptualised and a wide range of experiments in the Netherlands and abroad have been executed over the last couple of years. However,

  18. Risk assessment and clinical decision making for colorectal cancer screening.

    Science.gov (United States)

    Schroy, Paul C; Caron, Sarah E; Sherman, Bonnie J; Heeren, Timothy C; Battaglia, Tracy A

    2015-10-01

    Shared decision making (SDM) related to test preference has been advocated as a potentially effective strategy for increasing adherence to colorectal cancer (CRC) screening, yet primary care providers (PCPs) are often reluctant to comply with patient preferences if they differ from their own. Risk stratification advanced colorectal neoplasia (ACN) provides a rational strategy for reconciling these differences. To assess the importance of risk stratification in PCP decision making related to test preference for average-risk patients and receptivity to use of an electronic risk assessment tool for ACN to facilitate SDM. Mixed methods, including qualitative key informant interviews and a cross-sectional survey. PCPs at an urban, academic safety-net institution. Screening preferences, factors influencing patient recommendations and receptivity to use of a risk stratification tool. Nine PCPs participated in interviews and 57 completed the survey. Despite an overwhelming preference for colonoscopy by 95% of respondents, patient risk (67%) and patient preferences (63%) were more influential in their decision making than patient comorbidities (31%; P decision making, yet few providers considered risk factors other than age for average-risk patients. Providers were receptive to the use of a risk assessment tool for ACN when recommending an appropriate screening test for select patients. © 2013 John Wiley & Sons Ltd.

  19. Decision-theoretic planning of clinical patient management

    NARCIS (Netherlands)

    Peek, Niels Bastiaan

    2000-01-01

    When a doctor is treating a patient, he is constantly facing decisions. From the externally visible signs and symptoms he must establish a hypothesis of what might be wrong with the patient; then he must decide whether additional diagnostic procedures are required to verify this hypothesis,

  20. Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

    Science.gov (United States)

    Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

    2009-12-01

    In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

  1. SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

    International Nuclear Information System (INIS)

    Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M

    2016-01-01

    Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

  2. SU-G-206-01: A Fully Automated CT Tool to Facilitate Phantom Image QA for Quantitative Imaging in Clinical Trials

    Energy Technology Data Exchange (ETDEWEB)

    Wahi-Anwar, M; Lo, P; Kim, H; Brown, M; McNitt-Gray, M [UCLA Radiological Sciences, Los Angeles, CA (United States)

    2016-06-15

    Purpose: The use of Quantitative Imaging (QI) methods in Clinical Trials requires both verification of adherence to a specified protocol and an assessment of scanner performance under that protocol, which are currently accomplished manually. This work introduces automated phantom identification and image QA measure extraction towards a fully-automated CT phantom QA system to perform these functions and facilitate the use of Quantitative Imaging methods in clinical trials. Methods: This study used a retrospective cohort of CT phantom scans from existing clinical trial protocols - totaling 84 phantoms, across 3 phantom types using various scanners and protocols. The QA system identifies the input phantom scan through an ensemble of threshold-based classifiers. Each classifier - corresponding to a phantom type - contains a template slice, which is compared to the input scan on a slice-by-slice basis, resulting in slice-wise similarity metric values for each slice compared. Pre-trained thresholds (established from a training set of phantom images matching the template type) are used to filter the similarity distribution, and the slice with the most optimal local mean similarity, with local neighboring slices meeting the threshold requirement, is chosen as the classifier’s matched slice (if it existed). The classifier with the matched slice possessing the most optimal local mean similarity is then chosen as the ensemble’s best matching slice. If the best matching slice exists, image QA algorithm and ROIs corresponding to the matching classifier extracted the image QA measures. Results: Automated phantom identification performed with 84.5% accuracy and 88.8% sensitivity on 84 phantoms. Automated image quality measurements (following standard protocol) on identified water phantoms (n=35) matched user QA decisions with 100% accuracy. Conclusion: We provide a fullyautomated CT phantom QA system consistent with manual QA performance. Further work will include parallel

  3. Implementation of workflow engine technology to deliver basic clinical decision support functionality.

    Science.gov (United States)

    Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

    2011-04-10

    Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology

  4. Implementation of workflow engine technology to deliver basic clinical decision support functionality

    Science.gov (United States)

    2011-01-01

    Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of

  5. Clinical factors and the decision to transfuse chronic dialysis patients.

    Science.gov (United States)

    Whitman, Cynthia B; Shreay, Sanatan; Gitlin, Matthew; van Oijen, Martijn G H; Spiegel, Brennan M R

    2013-11-01

    Red blood cell transfusion was previously the principle therapy for anemia in CKD but became less prevalent after the introduction of erythropoiesis-stimulating agents. This study used adaptive choice-based conjoint analysis to identify preferences and predictors of transfusion decision-making in CKD. A computerized adaptive choice-based conjoint survey was administered between June and August of 2012 to nephrologists, internists, and hospitalists listed in the American Medical Association Masterfile. The survey quantified the relative importance of 10 patient attributes, including hemoglobin levels, age, occult blood in stool, severity of illness, eligibility for transplant, iron indices, erythropoiesis-stimulating agents, cardiovascular disease, and functional status. Triggers of transfusions in common dialysis scenarios were studied, and based on adaptive choice-based conjoint-derived preferences, relative importance by performing multivariable regression to identify predictors of transfusion preferences was assessed. A total of 350 providers completed the survey (n=305 nephrologists; mean age=46 years; 21% women). Of 10 attributes assessed, absolute hemoglobin level was the most important driver of transfusions, accounting for 29% of decision-making, followed by functional status (16%) and cardiovascular comorbidities (12%); 92% of providers transfused when hemoglobin was 7.5 g/dl, independent of other factors. In multivariable regression, Veterans Administration providers were more likely to transfuse at 8.0 g/dl (odds ratio, 5.9; 95% confidence interval, 1.9 to 18.4). Although transplant eligibility explained only 5% of decision-making, nephrologists were five times more likely to value it as important compared with non-nephrologists (odds ratio, 5.2; 95% confidence interval, 2.4 to 11.1). Adaptive choice-based conjoint analysis was useful in predicting influences on transfusion decisions. Hemoglobin level, functional status, and cardiovascular comorbidities

  6. [Clinical decision making and critical thinking in the nursing diagnostic process].

    Science.gov (United States)

    Müller-Staub, Maria

    2006-10-01

    The daily routine requires complex thinking processes of nurses, but clinical decision making and critical thinking are underestimated in nursing. A great demand for educational measures in clinical judgement related with the diagnostic process was found in nurses. The German literature hardly describes nursing diagnoses as clinical judgements about human reactions on health problems / life processes. Critical thinking is described as an intellectual, disciplined process of active conceptualisation, application and synthesis of information. It is gained through observation, experience, reflection and communication and leads thinking and action. Critical thinking influences the aspects of clinical decision making a) diagnostic judgement, b) therapeutic reasoning and c) ethical decision making. Human reactions are complex processes and in their course, human behavior is interpreted in the focus of health. Therefore, more attention should be given to the nursing diagnostic process. This article presents the theoretical framework of the paper "Clinical decision making: Fostering critical thinking in the nursing diagnostic process through case studies".

  7. User-centered design to improve clinical decision support in primary care.

    Science.gov (United States)

    Brunner, Julian; Chuang, Emmeline; Goldzweig, Caroline; Cain, Cindy L; Sugar, Catherine; Yano, Elizabeth M

    2017-08-01

    A growing literature has demonstrated the ability of user-centered design to make clinical decision support systems more effective and easier to use. However, studies of user-centered design have rarely examined more than a handful of sites at a time, and have frequently neglected the implementation climate and organizational resources that influence clinical decision support. The inclusion of such factors was identified by a systematic review as "the most important improvement that can be made in health IT evaluations." (1) Identify the prevalence of four user-centered design practices at United States Veterans Affairs (VA) primary care clinics and assess the perceived utility of clinical decision support at those clinics; (2) Evaluate the association between those user-centered design practices and the perceived utility of clinical decision support. We analyzed clinic-level survey data collected in 2006-2007 from 170 VA primary care clinics. We examined four user-centered design practices: 1) pilot testing, 2) provider satisfaction assessment, 3) formal usability assessment, and 4) analysis of impact on performance improvement. We used a regression model to evaluate the association between user-centered design practices and the perceived utility of clinical decision support, while accounting for other important factors at those clinics, including implementation climate, available resources, and structural characteristics. We also examined associations separately at community-based clinics and at hospital-based clinics. User-centered design practices for clinical decision support varied across clinics: 74% conducted pilot testing, 62% conducted provider satisfaction assessment, 36% conducted a formal usability assessment, and 79% conducted an analysis of impact on performance improvement. Overall perceived utility of clinical decision support was high, with a mean rating of 4.17 (±.67) out of 5 on a composite measure. "Analysis of impact on performance

  8. Clinical data warehousing for evidence based decision making.

    Science.gov (United States)

    Narra, Lekha; Sahama, Tony; Stapleton, Peta

    2015-01-01

    Large volumes of heterogeneous health data silos pose a big challenge when exploring for information to allow for evidence based decision making and ensuring quality outcomes. In this paper, we present a proof of concept for adopting data warehousing technology to aggregate and analyse disparate health data in order to understand the impact various lifestyle factors on obesity. We present a practical model for data warehousing with detailed explanation which can be adopted similarly for studying various other health issues.

  9. Ontology-based clinical decision support system applied on diabetes

    OpenAIRE

    Mukabunani, Alphonsine

    2017-01-01

    Master's thesis Information- and communication technology IKT590 - University of Agder 2017 Medical diagnosis is a multi-step process which is complex as it requires the consideration of many factors. Additionally, the accuracy of diagnosis varies depending on the skill and knowledge a physician has in the medical field. Using ICT solution, the physicians can be assisted so that they can make an accurate decision. Many applications have been developed to enhance physician performance and i...

  10. Strategies to facilitate shared decision-making about pediatric oncology clinical trial enrollment: A systematic review.

    Science.gov (United States)

    Robertson, Eden G; Wakefield, Claire E; Signorelli, Christina; Cohn, Richard J; Patenaude, Andrea; Foster, Claire; Pettit, Tristan; Fardell, Joanna E

    2018-07-01

    We conducted a systematic review to identify the strategies that have been recommended in the literature to facilitate shared decision-making regarding enrolment in pediatric oncology clinical trials. We searched seven databases for peer-reviewed literature, published 1990-2017. Of 924 articles identified, 17 studies were eligible for the review. We assessed study quality using the 'Mixed-Methods Appraisal Tool'. We coded the results and discussions of papers line-by-line using nVivo software. We categorized strategies thematically. Five main themes emerged: 1) decision-making as a process, 2) individuality of the process; 3) information provision, 4) the role of communication, or 5) decision and psychosocial support. Families should have adequate time to make a decision. HCPs should elicit parents' and patients' preferences for level of information and decision involvement. Information should be clear and provided in multiple modalities. Articles also recommended providing training for healthcare professionals and access to psychosocial support for families. High quality, individually-tailored information, open communication and psychosocial support appear vital in supporting decision-making regarding enrollment in clinical trials. These data will usefully inform future decision-making interventions/tools to support families making clinical trial decisions. A solid evidence-base for effective strategies which facilitate shared decision-making is needed. Copyright © 2018 Elsevier B.V. All rights reserved.

  11. mHealth for Clinical Decision-Making in Sub-Saharan Africa : A Scoping Review

    NARCIS (Netherlands)

    Adepoju, Ibukun-Oluwa Omolade; Albersen, Bregje Joanna Antonia; De Brouwere, Vincent; van Roosmalen, Jos; Zweekhorst, M.B.M.

    2017-01-01

    BACKGROUND: In a bid to deliver quality health services in resource-poor settings, mobile health (mHealth) is increasingly being adopted. The role of mHealth in facilitating evidence-based clinical decision-making through data collection, decision algorithms, and evidence-based guidelines, for

  12. Complexity perspectives on clinical decision making in an intensive care unit

    NARCIS (Netherlands)

    De Bock, Ben A.; Willems, Dick L.; Weinstein, Henry C.

    2017-01-01

    How to clarify the implications of complexity thinking for decision making in the intensive care unit (ICU)? Retrospective qualitative empirical research. Practitioners in an ICU were interviewed on how their decisions were made regarding a particular patient in a difficult, clinical situation.

  13. Disciplined Decision Making in an Interdisciplinary Environment: Some Implications for Clinical Applications of Statistical Process Control.

    Science.gov (United States)

    Hantula, Donald A.

    1995-01-01

    Clinical applications of statistical process control (SPC) in human service organizations are considered. SPC is seen as providing a standard set of criteria that serves as a common interface for data-based decision making, which may bring decision making under the control of established contingencies rather than the immediate contingencies of…

  14. Towards patient-centered colorectal cancer surgery : focus on risks, decisions and clinical auditing

    NARCIS (Netherlands)

    Snijders, Heleen Simone

    2014-01-01

    The aim of this thesis was to explore several aspects of both clinical decision making and quality assessment in colorectal cancer surgery. Part one focusses on benefits and risks of treatment options, preoperative information provision and Shared Decision Making (SDM); part two investigates changes

  15. Factors Predicting Oncology Care Providers' Behavioral Intention to Adopt Clinical Decision Support Systems

    Science.gov (United States)

    Wolfenden, Andrew

    2012-01-01

    The purpose of this quantitative correlation study was to examine the predictors of user behavioral intention on the decision of oncology care providers to adopt or reject the clinical decision support system. The Unified Theory of Acceptance and Use of Technology (UTAUT) formed the foundation of the research model and survey instrument. The…

  16. Development of a computer-based automated pure tone hearing screening device: a preliminary clinical trial.

    Science.gov (United States)

    Gan, Kok Beng; Azeez, Dhifaf; Umat, Cila; Ali, Mohd Alauddin Mohd; Wahab, Noor Alaudin Abdul; Mukari, Siti Zamratol Mai-Sarah

    2012-10-01

    Hearing screening is important for the early detection of hearing loss. The requirements of specialized equipment, skilled personnel, and quiet environments for valid screening results limit its application in schools and health clinics. This study aimed to develop an automated hearing screening kit (auto-kit) with the capability of realtime noise level monitoring to ensure that the screening is performed in an environment that conforms to the standard. The auto-kit consists of a laptop, a 24-bit resolution sound card, headphones, a microphone, and a graphical user interface, which is calibrated according to the American National Standards Institute S3.6-2004 standard. The auto-kit can present four test tones (500, 1000, 2000, and 4000 Hz) at 25 or 40 dB HL screening cut-off level. The clinical results at 40 dB HL screening cut-off level showed that the auto-kit has a sensitivity of 92.5% and a specificity of 75.0%. Because the 500 Hz test tone is not included in the standard hearing screening procedure, it can be excluded from the auto-kit test procedure. The exclusion of 500 Hz test tone improved the specificity of the auto-kit from 75.0% to 92.3%, which suggests that the auto-kit could be a valid hearing screening device. In conclusion, the auto-kit may be a valuable hearing screening tool, especially in countries where resources are limited.

  17. Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach

    OpenAIRE

    Bennett, Casey C.; Hauser, Kris

    2013-01-01

    In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This serves two potential functions: 1) a simulation environment for expl...

  18. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: Methods of a decision-maker-researcher partnership systematic review

    OpenAIRE

    Wilczynski Nancy L; Haynes R Brian

    2010-01-01

    Abstract Background Computerized clinical decision support systems are information technology-based systems designed to improve clinical decision-making. As with any healthcare intervention with claims to improve process of care or patient outcomes, decision support systems should be rigorously evaluated before widespread dissemination into clinical practice. Engaging healthcare providers and managers in the review process may facilitate knowledge translation and uptake. The objective of this...

  19. The impact of an electronic clinical decision support for pulmonary ...

    African Journals Online (AJOL)

    emergency unit were positive for PE. ... technology. ... 1 Division of Radiodiagnosis, Department of Medical Imaging and Clinical Oncology, Faculty of Medicine and ... Stellenbosch University and Tygerberg Hospital, Cape Town, South Africa.

  20. The role of emotion in clinical decision making: an integrative literature review

    OpenAIRE

    Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

    2017-01-01

    Background Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. Methods A systematic search of the bibliographic databases PubMed,...

  1. Preferred information sources for clinical decision making: critical care nurses' perceptions of information accessibility and usefulness.

    Science.gov (United States)

    Marshall, Andrea P; West, Sandra H; Aitken, Leanne M

    2011-12-01

    Variability in clinical practice may result from the use of diverse information sources to guide clinical decisions. In routine clinical practice, nurses privilege information from colleagues over more formal information sources. It is not clear whether similar information-seeking behaviour is exhibited when critical care nurses make decisions about a specific clinical practice, where extensive practice variability exists alongside a developing research base. This study explored the preferred sources of information intensive care nurses used and their perceptions of the accessibility and usefulness of this information for making decisions in clinically uncertain situations specific to enteral feeding practice. An instrumental case study design, incorporating concurrent verbal protocols, Q methodology and focus groups, was used to determine intensive care nurses' perspectives of information use in the resolution of clinical uncertainty. A preference for information from colleagues to support clinical decisions was observed. People as information sources were considered most useful and most accessible in the clinical setting. Text and electronic information sources were seen as less accessible, mainly because of the time required to access the information within the documents. When faced with clinical uncertainty, obtaining information from colleagues allows information to be quickly accessed and applied within the context of a specific clinical presentation. Seeking information from others also provides opportunities for shared decision-making and potential validation of clinical judgment, although differing views may exacerbate clinical uncertainty. The social exchange of clinical information may meet the needs of nurses working in a complex, time-pressured environment but the extent of the evidence base for information passed through verbal communication is unclear. The perceived usefulness and accessibility of information is premised on the ease of use and access

  2. Development and evaluation of learning module on clinical decision-making in Prosthodontics.

    Science.gov (United States)

    Deshpande, Saee; Lambade, Dipti; Chahande, Jayashree

    2015-01-01

    Best practice strategies for helping students learn the reasoning skills of problem solving and critical thinking (CT) remain a source of conjecture, particularly with regard to CT. The dental education literature is fundamentally devoid of research on the cognitive components of clinical decision-making. This study was aimed to develop and evaluate the impact of blended learning module on clinical decision-making skills of dental graduates for planning prosthodontics rehabilitation. An interactive teaching module consisting of didactic lectures on clinical decision-making and a computer-assisted case-based treatment planning software was developed Its impact on cognitive knowledge gain in clinical decision-making was evaluated using an assessment involving problem-based multiple choice questions and paper-based case scenarios. Mean test scores were: Pretest (17 ± 1), posttest 1 (21 ± 2) and posttest 2 (43 ± 3). Comparison of mean scores was done with one-way ANOVA test. There was overall significant difference in between mean scores at all the three points (P posttest 1 > pretest. Blended teaching methods employing didactic lectures on the clinical decision-making as well as computer assisted case-based learning can be used to improve quality of clinical decision-making in prosthodontic rehabilitation for dental graduates.

  3. Accuracy of intuition in clinical decision-making among novice clinicians.

    Science.gov (United States)

    Price, Amanda; Zulkosky, Kristen; White, Krista; Pretz, Jean

    2017-05-01

    To assess the reliance on intuitive and analytical approaches during clinical decision-making among novice clinicians and whether that reliance is associated with accurate decision-making. Nurse educators and managers tend to emphasize analysis over intuition during clinical decision-making though nurses typically report some reliance on intuition in their practice. We hypothesized that under certain conditions, reliance on intuition would support accurate decision-making, even among novices. This study utilized an experimental design with clinical complication (familiar vs. novel) and decision phase (cue acquisition, diagnosis and action) as within-subjects' factors, and simulation role (observer, family, auxiliary nurse and primary nurse) as between-subjects' factor. We examined clinical decision-making accuracy among final semester pre-licensure nursing students in a simulation experience. Students recorded their reasoning about emerging clinical complications with their patient during two distinct points in the simulation; one point involved a familiar complication and the other a relatively novel complication. All data were collected during Spring 2015. Although most participants relied more heavily on analysis than on intuition, use of intuition during the familiar complication was associated with more accurate decision-making, particularly in guiding attention to relevant cues. With the novel complication, use of intuition appeared to hamper decision-making, particularly for those in an observer role. Novice clinicians should be supported by educators and nurse managers to note when their intuitions are likely to be valid. Our findings emphasize the integrated nature of intuition and analysis in clinical decision-making. © 2016 John Wiley & Sons Ltd.

  4. Automation in an Addiction Treatment Research Clinic: Computerized Contingency Management, Ecological Momentary Assessment, and a Protocol Workflow System

    Science.gov (United States)

    Vahabzadeh, Massoud; Lin, Jia-Ling; Mezghanni, Mustapha; Epstein, David H.; Preston, Kenzie L.

    2009-01-01

    Issues A challenge in treatment research is the necessity of adhering to protocol and regulatory strictures while maintaining flexibility to meet patients’ treatment needs and accommodate variations among protocols. Another challenge is the acquisition of large amounts of data in an occasionally hectic environment, along with provision of seamless methods for exporting, mining, and querying the data. Approach We have automated several major functions of our outpatient treatment research clinic for studies in drug abuse and dependence. Here we describe three such specialized applications: the Automated Contingency Management (ACM) system for delivery of behavioral interventions, the Transactional Electronic Diary (TED) system for management of behavioral assessments, and the Protocol Workflow System (PWS) for computerized workflow automation and guidance of each participant’s daily clinic activities. These modules are integrated into our larger information system to enable data sharing in real time among authorized staff. Key Findings ACM and TED have each permitted us to conduct research that was not previously possible. In addition, the time to data analysis at the end of each study is substantially shorter. With the implementation of the PWS, we have been able to manage a research clinic with an 80-patient capacity having an annual average of 18,000 patient-visits and 7,300 urine collections with a research staff of five. Finally, automated data management has considerably enhanced our ability to monitor and summarize participant-safety data for research oversight. Implications and conclusion When developed in consultation with end users, automation in treatment-research clinics can enable more efficient operations, better communication among staff, and expansions in research methods. PMID:19320669

  5. SU-G-TeP1-05: Development and Clinical Introduction of Automated Radiotherapy Treatment Planning for Prostate Cancer

    International Nuclear Information System (INIS)

    Winkel, D; Bol, GH; Asselen, B van; Hes, J; Scholten, V; Kerkmeijer, LGW; Raaymakers, BW

    2016-01-01

    Purpose: To develop an automated radiotherapy treatment planning and optimization workflow for prostate cancer in order to generate clinical treatment plans. Methods: A fully automated radiotherapy treatment planning and optimization workflow was developed based on the treatment planning system Monaco (Elekta AB, Stockholm, Sweden). To evaluate our method, a retrospective planning study (n=100) was performed on patients treated for prostate cancer with 5 field intensity modulated radiotherapy, receiving a dose of 35×2Gy to the prostate and vesicles and a simultaneous integrated boost of 35×0.2Gy to the prostate only. A comparison was made between the dosimetric values of the automatically and manually generated plans. Operator time to generate a plan and plan efficiency was measured. Results: A comparison of the dosimetric values show that automatically generated plans yield more beneficial dosimetric values. In automatic plans reductions of 43% in the V72Gy of the rectum and 13% in the V72Gy of the bladder are observed when compared to the manually generated plans. Smaller variance in dosimetric values is seen, i.e. the intra- and interplanner variability is decreased. For 97% of the automatically generated plans and 86% of the clinical plans all criteria for target coverage and organs at risk constraints are met. The amount of plan segments and monitor units is reduced by 13% and 9% respectively. Automated planning requires less than one minute of operator time compared to over an hour for manual planning. Conclusion: The automatically generated plans are highly suitable for clinical use. The plans have less variance and a large gain in time efficiency has been achieved. Currently, a pilot study is performed, comparing the preference of the clinician and clinical physicist for the automatic versus manual plan. Future work will include expanding our automated treatment planning method to other tumor sites and develop other automated radiotherapy workflows.

  6. Automation in an addiction treatment research clinic: computerised contingency management, ecological momentary assessment and a protocol workflow system.

    Science.gov (United States)

    Vahabzadeh, Massoud; Lin, Jia-Ling; Mezghanni, Mustapha; Epstein, David H; Preston, Kenzie L

    2009-01-01

    A challenge in treatment research is the necessity of adhering to protocol and regulatory strictures while maintaining flexibility to meet patients' treatment needs and to accommodate variations among protocols. Another challenge is the acquisition of large amounts of data in an occasionally hectic environment, along with the provision of seamless methods for exporting, mining and querying the data. We have automated several major functions of our outpatient treatment research clinic for studies in drug abuse and dependence. Here we describe three such specialised applications: the Automated Contingency Management (ACM) system for the delivery of behavioural interventions, the transactional electronic diary (TED) system for the management of behavioural assessments and the Protocol Workflow System (PWS) for computerised workflow automation and guidance of each participant's daily clinic activities. These modules are integrated into our larger information system to enable data sharing in real time among authorised staff. ACM and the TED have each permitted us to conduct research that was not previously possible. In addition, the time to data analysis at the end of each study is substantially shorter. With the implementation of the PWS, we have been able to manage a research clinic with an 80 patient capacity, having an annual average of 18,000 patient visits and 7300 urine collections with a research staff of five. Finally, automated data management has considerably enhanced our ability to monitor and summarise participant safety data for research oversight. When developed in consultation with end users, automation in treatment research clinics can enable more efficient operations, better communication among staff and expansions in research methods.

  7. MODULAR ANALYTICS: A New Approach to Automation in the Clinical Laboratory.

    Science.gov (United States)

    Horowitz, Gary L; Zaman, Zahur; Blanckaert, Norbert J C; Chan, Daniel W; Dubois, Jeffrey A; Golaz, Olivier; Mensi, Noury; Keller, Franz; Stolz, Herbert; Klingler, Karl; Marocchi, Alessandro; Prencipe, Lorenzo; McLawhon, Ronald W; Nilsen, Olaug L; Oellerich, Michael; Luthe, Hilmar; Orsonneau, Jean-Luc; Richeux, Gérard; Recio, Fernando; Roldan, Esther; Rymo, Lars; Wicktorsson, Anne-Charlotte; Welch, Shirley L; Wieland, Heinrich; Grawitz, Andrea Busse; Mitsumaki, Hiroshi; McGovern, Margaret; Ng, Katherine; Stockmann, Wolfgang

    2005-01-01

    MODULAR ANALYTICS (Roche Diagnostics) (MODULAR ANALYTICS, Elecsys and Cobas Integra are trademarks of a member of the Roche Group) represents a new approach to automation for the clinical chemistry laboratory. It consists of a control unit, a core unit with a bidirectional multitrack rack transportation system, and three distinct kinds of analytical modules: an ISE module, a P800 module (44 photometric tests, throughput of up to 800 tests/h), and a D2400 module (16 photometric tests, throughput up to 2400 tests/h). MODULAR ANALYTICS allows customised configurations for various laboratory workloads. The performance and practicability of MODULAR ANALYTICS were evaluated in an international multicentre study at 16 sites. Studies included precision, accuracy, analytical range, carry-over, and workflow assessment. More than 700 000 results were obtained during the course of the study. Median between-day CVs were typically less than 3% for clinical chemistries and less than 6% for homogeneous immunoassays. Median recoveries for nearly all standardised reference materials were within 5% of assigned values. Method comparisons versus current existing routine instrumentation were clinically acceptable in all cases. During the workflow studies, the work from three to four single workstations was transferred to MODULAR ANALYTICS, which offered over 100 possible methods, with reduction in sample splitting, handling errors, and turnaround time. Typical sample processing time on MODULAR ANALYTICS was less than 30 minutes, an improvement from the current laboratory systems. By combining multiple analytic units in flexible ways, MODULAR ANALYTICS met diverse laboratory needs and offered improvement in workflow over current laboratory situations. It increased overall efficiency while maintaining (or improving) quality.

  8. Automated identification of diagnosis and co-morbidity in clinical records.

    Science.gov (United States)

    Cano, C; Blanco, A; Peshkin, L

    2009-01-01

    Automated understanding of clinical records is a challenging task involving various legal and technical difficulties. Clinical free text is inherently redundant, unstructured, and full of acronyms, abbreviations and domain-specific language which make it challenging to mine automatically. There is much effort in the field focused on creating specialized ontology, lexicons and heuristics based on expert knowledge of the domain. However, ad-hoc solutions poorly generalize across diseases or diagnoses. This paper presents a successful approach for a rapid prototyping of a diagnosis classifier based on a popular computational linguistics platform. The corpus consists of several hundred of full length discharge summaries provided by Partners Healthcare. The goal is to identify a diagnosis and assign co-morbidi-ty. Our approach is based on the rapid implementation of a logistic regression classifier using an existing toolkit: LingPipe (http://alias-i.com/lingpipe). We implement and compare three different classifiers. The baseline approach uses character 5-grams as features. The second approach uses a bag-of-words representation enriched with a small additional set of features. The third approach reduces a feature set to the most informative features according to the information content. The proposed systems achieve high performance (average F-micro 0.92) for the task. We discuss the relative merit of the three classifiers. Supplementary material with detailed results is available at: http:// decsai.ugr.es/~ccano/LR/supplementary_ material/ We show that our methodology for rapid prototyping of a domain-unaware system is effective for building an accurate classifier for clinical records.

  9. Fully automated atlas-based hippocampal volumetry for detection of Alzheimer's disease in a memory clinic setting.

    Science.gov (United States)

    Suppa, Per; Anker, Ulrich; Spies, Lothar; Bopp, Irene; Rüegger-Frey, Brigitte; Klaghofer, Richard; Gocke, Carola; Hampel, Harald; Beck, Sacha; Buchert, Ralph

    2015-01-01

    Hippocampal volume is a promising biomarker to enhance the accuracy of the diagnosis of dementia due to Alzheimer's disease (AD). However, whereas hippocampal volume is well studied in patient samples from clinical trials, its value in clinical routine patient care is still rather unclear. The aim of the present study, therefore, was to evaluate fully automated atlas-based hippocampal volumetry for detection of AD in the setting of a secondary care expert memory clinic for outpatients. One-hundred consecutive patients with memory complaints were clinically evaluated and categorized into three diagnostic groups: AD, intermediate AD, and non-AD. A software tool based on open source software (Statistical Parametric Mapping SPM8) was employed for fully automated tissue segmentation and stereotactical normalization of high-resolution three-dimensional T1-weighted magnetic resonance images. Predefined standard masks were used for computation of grey matter volume of the left and right hippocampus which then was scaled to the patient's total grey matter volume. The right hippocampal volume provided an area under the receiver operating characteristic curve of 84% for detection of AD patients in the whole sample. This indicates that fully automated MR-based hippocampal volumetry fulfills the requirements for a relevant core feasible biomarker for detection of AD in everyday patient care in a secondary care memory clinic for outpatients. The software used in the present study has been made freely available as an SPM8 toolbox. It is robust and fast so that it is easily integrated into routine workflow.

  10. Evidence-Based Clinical Decision: Key to Improved Patients Care ...

    African Journals Online (AJOL)

    ... materials remain limited to mostly developed countries. There is need to adopt measures to further facilitate dissemination of current information of effective health to care providers and policymakers in resource-poor countries. This review is aimed at re-enforcing the need for applying best-evidence into clinical practice

  11. Detecting fast, online reasoning processes in clinical decision making.

    Science.gov (United States)

    Flores, Amanda; Cobos, Pedro L; López, Francisco J; Godoy, Antonio

    2014-06-01

    In an experiment that used the inconsistency paradigm, experienced clinical psychologists and psychology students performed a reading task using clinical reports and a diagnostic judgment task. The clinical reports provided information about the symptoms of hypothetical clients who had been previously diagnosed with a specific mental disorder. Reading times of inconsistent target sentences were slower than those of control sentences, demonstrating an inconsistency effect. The results also showed that experienced clinicians gave different weights to different symptoms according to their relevance when fluently reading the clinical reports provided, despite the fact that all the symptoms were of equal diagnostic value according to the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; American Psychiatric Association, 2000). The diagnostic judgment task yielded a similar pattern of results. In contrast to previous findings, the results of the reading task may be taken as direct evidence of the intervention of reasoning processes that occur very early, rapidly, and online. We suggest that these processes are based on the representation of mental disorders and that these representations are particularly suited to fast retrieval from memory and to making inferences. They may also be related to the clinicians' causal reasoning. The implications of these results for clinician training are also discussed.

  12. Information management to enable personalized medicine: stakeholder roles in building clinical decision support.

    Science.gov (United States)

    Downing, Gregory J; Boyle, Scott N; Brinner, Kristin M; Osheroff, Jerome A

    2009-10-08

    Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized

  13. Information management to enable personalized medicine: stakeholder roles in building clinical decision support

    Directory of Open Access Journals (Sweden)

    Brinner Kristin M

    2009-10-01

    Full Text Available Abstract Background Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies. Discussion Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures, and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine. Summary This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In

  14. Effects of reflection on clinical decision-making of intensive care unit nurses.

    Science.gov (United States)

    Razieh, Shahrokhi; Somayeh, Ghafari; Fariba, Haghani

    2018-07-01

    Nurses are one of the most influential factors in overcoming the main challenges faced by health systems throughout the world. Every health system should, hence, empower nurses in clinical judgment and decision-making skills. This study evaluated the effects of implementing Tanner's reflection method on clinical decision-making of nurses working in an intensive care unit (ICU). This study used an experimental, pretest, posttest design. The setting was the intensive care unit of Amin Hospital Isfahan, Iran. The convenience sample included 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). This clinical trial was performed on 60 nurses working in the ICU of Amin Hospital (Isfahan, Iran). The nurses were selected by census sampling and randomly allocated to either the case or the control group. Data were collected using a questionnaire containing demographic characteristics and the clinical decision-making scale developed by Laurie and Salantera (NDMI-14). The questionnaire was completed before and one week after the intervention. The data were analyzed using SPSS 21.0. The two groups were not significantly different in terms of the level and mean scores of clinical decision-making before the intervention (P = 0.786). Based on the results of independent t-test, the mean score of clinical decision-making one week after the intervention was significantly higher in the case group than in the control group (P = 0.009; t = -2.69). The results of Mann Whitney test showed that one week after the intervention, the nurses' level of clinical decision-making in the case group rose to the next level (P = 0.001). Reflection could improve the clinical decision-making of ICU nurses. It is, thus, recommended to incorporate this method into the nursing curriculum and care practices. Copyright © 2018. Published by Elsevier Ltd.

  15. Exploring the use of Option Grid™ patient decision aids in a sample of clinics in Poland.

    Science.gov (United States)

    Scalia, Peter; Elwyn, Glyn; Barr, Paul; Song, Julia; Zisman-Ilani, Yaara; Lesniak, Monika; Mullin, Sarah; Kurek, Krzysztof; Bushell, Matt; Durand, Marie-Anne

    2018-05-29

    Research on the implementation of patient decision aids to facilitate shared decision making in clinical settings has steadily increased across Western countries. A study which implements decision aids and measures their impact on shared decision making has yet to be conducted in the Eastern part of Europe. To study the use of Option Grid TM patient decision aids in a sample of Grupa LUX MED clinics in Warsaw, Poland, and measure their impact on shared decision making. We conducted a pre-post interventional study. Following a three-month period of usual care, clinicians from three Grupa LUX MED clinics received a one-hour training session on how to use three Option Grid TM decision aids and were provided with copies for use for four months. Throughout the study, all eligible patients were asked to complete the three-item CollaboRATE patient-reported measure of shared decision making after their clinical encounter. CollaboRATE enables patients to assess the efforts clinicians make to: (i) inform them about their health issues; (ii) listen to 'what matters most'; (iii) integrate their treatment preference in future plans. A Hierarchical Logistic Regression model was performed to understand which variables had an effect on CollaboRATE. 2,048 patients participated in the baseline phase; 1,889 patients participated in the intervention phase. Five of the thirteen study clinicians had a statistically significant increase in their CollaboRATE scores (pOption Grid TM helped some clinicians practice shared decision making as reflected in CollaboRATE scores, but most clinicians did not have a significant increase in their scores. Our study indicates that the effect of these interventions may be dependent on clinic contexts and clinician engagement. Copyright © 2018. Published by Elsevier GmbH.

  16. [Knowledge management system for laboratory work and clinical decision support].

    Science.gov (United States)

    Inada, Masanori; Sato, Mayumi; Yoneyama, Akiko

    2011-05-01

    This paper discusses a knowledge management system for clinical laboratories. In the clinical laboratory of Toranomon Hospital, we receive about 20 questions relevant to laboratory tests per day from medical doctors or co-medical staff. These questions mostly involve the essence to appropriately accomplish laboratory tests. We have to answer them carefully and suitably because an incorrect answer may cause a medical accident. Up to now, no method has been in place to achieve a rapid response and standardized answers. For this reason, the laboratory staff have responded to various questions based on their individual knowledge. We began to develop a knowledge management system to promote the knowledge of staff working for the laboratory. This system is a type of knowledge base for assisting the work, such as inquiry management, laboratory consultation, process management, and clinical support. It consists of several functions: guiding laboratory test information, managing inquiries from medical staff, reporting results of patient consultation, distributing laboratory staffs notes, and recording guidelines for laboratory medicine. The laboratory test information guide has 2,000 records of medical test information registered in the database with flexible retrieval. The inquiry management tool provides a methos to record all questions, answer easily, and retrieve cases. It helps staff to respond appropriately in a short period of time. The consulting report system treats patients' claims regarding medical tests. The laboratory staffs notes enter a file management system so they can be accessed to aid in clinical support. Knowledge sharing using this function can achieve the transition from individual to organizational learning. Storing guidelines for laboratory medicine will support EBM. Finally, it is expected that this system will support intellectual activity concerning laboratory work and contribute to the practice of knowledge management for clinical work support.

  17. Automated percutaneous lumbar discectomy: technique, indications and clinical follow-up in over 1000 patients

    Energy Technology Data Exchange (ETDEWEB)

    Bonaldi, G. [Department of Neuroradiology, Ospedali Riuniti, Bergamo (Italy)

    2003-10-01

    This paper summarises my experience, over 14 years, treating over 1350 patients suffering from lumbar disc pathology, using minimally invasive intradiscal decompressive percutaneous techniques. The vast majority underwent the method introduced by Onik in 1985, referred to as ''automated'' since it involves a mechanical probe, working by a ''suction and cutting'' action for removal of the nucleus pulposus. Postoperative follow-up of at least 6 months was available for 1047 patients aged 15-92 years, who underwent this procedure up to June 2002. Results, based on a patient satisfaction, have been good in 58% of patients at 2 months and in 67.5% at 6 months; they have been particularly favourable in some subgroups such as elderly people (79.5% of excellent or good results), patients previously operated upon (78%) and those with ''discogenic'' low back pain (79%). Complication rates have been extremely low (less than 1%) and all complications cleared up without sequelae. In comparison with other percutaneous disc treatments, Onik's achieves the best compromise between clinical efficacy, comfort for the patient and low invasiveness. (orig.)

  18. Bystander Automated External Defibrillator Use and Clinical Outcomes after Out-of-Hospital Cardiac Arrest

    DEFF Research Database (Denmark)

    Holmberg, Mathias J; Vognsen, Mikael; Andersen, Mikkel S

    2017-01-01

    Aim: To systematically review studies comparing bystander automated external defibrillator (AED) use to no AED use in regard to clinical outcomes in out-of-hospital cardiac arrest (OHCA), and to provide a descriptive summary of studies on the cost-effectiveness of bystander AED use. Methods: We...... randomized trials, and 13 cost-effectiveness studies were included. Meta-analysis of 6 observational studies without critical risk of bias showed that bystander AED use was associated with survival to hospital discharge (all rhythms OR: 1.73 [95% CI: 1.36, 2.18], shockable rhythms OR: 1.66 [95% CI: 1.54, 1.......79]) and favorable neurological outcome (all rhythms OR: 2.12 [95% CI: 1.36, 3.29], shockable rhythms OR: 2.37 [95% CI: 1.58, 3.57]). There was no association between bystander AED use and neurological outcome for non-shockable rhythms (OR: 0.76 [95% CI: 0.10, 5.87]). The Public-Access Defibrillation trial found...

  19. Automated customized retrieval of radiotherapy data for clinical trials, audit and research.

    Science.gov (United States)

    Romanchikova, Marina; Harrison, Karl; Burnet, Neil G; Hoole, Andrew Cf; Sutcliffe, Michael Pf; Parker, Michael Andrew; Jena, Rajesh; Thomas, Simon James

    2018-02-01

    To enable fast and customizable automated collection of radiotherapy (RT) data from tomotherapy storage. Human-readable data maps (TagMaps) were created to generate DICOM-RT (Digital Imaging and Communications in Medicine standard for Radiation Therapy) data from tomotherapy archives, and provided access to "hidden" information comprising delivery sinograms, positional corrections and adaptive-RT doses. 797 data sets totalling 25,000 scans were batch-exported in 31.5 h. All archived information was restored, including the data not available via commercial software. The exported data were DICOM-compliant and compatible with major commercial tools including RayStation, Pinnacle and ProSoma. The export ran without operator interventions. The TagMap method for DICOM-RT data modelling produced software that was many times faster than the vendor's solution, required minimal operator input and delivered high volumes of vendor-identical DICOM data. The approach is applicable to many clinical and research data processing scenarios and can be adapted to recover DICOM-RT data from other proprietary storage types such as Elekta, Pinnacle or ProSoma. Advances in knowledge: A novel method to translate data from proprietary storage to DICOM-RT is presented. It provides access to the data hidden in electronic archives, offers a working solution to the issues of data migration and vendor lock-in and paves the way for large-scale imaging and radiomics studies.

  20. Managing risk: clinical decision-making in mental health services.

    Science.gov (United States)

    Muir-Cochrane, Eimear; Gerace, Adam; Mosel, Krista; O'Kane, Debra; Barkway, Patricia; Curren, David; Oster, Candice

    2011-01-01

    Risk assessment and management is a major component of contemporary mental health practice. Risk assessment in health care exists within contemporary perspectives of management and risk aversive practices in health care. This has led to much discussion about the best approach to assessing possible risks posed by people with mental health problems. In addition, researchers and commentators have expressed concern that clinical practice is being dominated by managerial models of risk management at the expense of meeting the patient's health and social care needs. The purpose of the present study is to investigate the risk assessment practices of a multidisciplinary mental health service. Findings indicate that mental health professionals draw on both managerial and therapeutic approaches to risk management, integrating these approaches into their clinical practice. Rather than being dominated by managerial concerns regarding risk, the participants demonstrate professional autonomy and concern for the needs of their clients.

  1. Automation of CT-based haemorrhagic stroke assessment for improved clinical outcomes: study protocol and design.

    Science.gov (United States)

    Chinda, Betty; Medvedev, George; Siu, William; Ester, Martin; Arab, Ali; Gu, Tao; Moreno, Sylvain; D'Arcy, Ryan C N; Song, Xiaowei

    2018-04-19

    Haemorrhagic stroke is of significant healthcare concern due to its association with high mortality and lasting impact on the survivors' quality of life. Treatment decisions and clinical outcomes depend strongly on the size, spread and location of the haematoma. Non-contrast CT (NCCT) is the primary neuroimaging modality for haematoma assessment in haemorrhagic stroke diagnosis. Current procedures do not allow convenient NCCT-based haemorrhage volume calculation in clinical settings, while research-based approaches are yet to be tested for clinical utility; there is a demonstrated need for developing effective solutions. The project under review investigates the development of an automatic NCCT-based haematoma computation tool in support of accurate quantification of haematoma volumes. Several existing research methods for haematoma volume estimation are studied. Selected methods are tested using NCCT images of patients diagnosed with acute haemorrhagic stroke. For inter-rater and intrarater reliability evaluation, different raters will analyse haemorrhage volumes independently. The efficiency with respect to time of haematoma volume assessments will be examined to compare with the results from routine clinical evaluations and planimetry assessment that are known to be more accurate. The project will target the development of an enhanced solution by adapting existing methods and integrating machine learning algorithms. NCCT-based information of brain haemorrhage (eg, size, volume, location) and other relevant information (eg, age, sex, risk factor, comorbidities) will be used in relation to clinical outcomes with future project development. Validity and reliability of the solution will be examined for potential clinical utility. The project including procedures for deidentification of NCCT data has been ethically approved. The study involves secondary use of existing data and does not require new consent of participation. The team consists of clinical neuroimaging

  2. Clinical decision-making and therapeutic approaches in osteopathy - a qualitative grounded theory study.

    Science.gov (United States)

    Thomson, Oliver P; Petty, Nicola J; Moore, Ann P

    2014-02-01

    There is limited understanding of how osteopaths make decisions in relation to clinical practice. The aim of this research was to construct an explanatory theory of the clinical decision-making and therapeutic approaches of experienced osteopaths in the UK. Twelve UK registered osteopaths participated in this constructivist grounded theory qualitative study. Purposive and theoretical sampling was used to select participants. Data was collected using semi-structured interviews which were audio-recorded and transcribed. As the study approached theoretical sufficiency, participants were observed and video-recorded during a patient appointment, which was followed by a video-prompted interview. Constant comparative analysis was used to analyse and code data. Data analysis resulted in the construction of three qualitatively different therapeutic approaches which characterised participants and their clinical practice, termed; Treater, Communicator and Educator. Participants' therapeutic approach influenced their approach to clinical decision-making, the level of patient involvement, their interaction with patients, and therapeutic goals. Participants' overall conception of practice lay on a continuum ranging from technical rationality to professional artistry, and contributed to their therapeutic approach. A range of factors were identified which influenced participants' conception of practice. The findings indicate that there is variation in osteopaths' therapeutic approaches to practice and clinical decision-making, which are influenced by their overall conception of practice. This study provides the first explanatory theory of the clinical decision-making and therapeutic approaches of osteopaths. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. The value of participatory development to support antimicrobial stewardship with a clinical decision support system

    NARCIS (Netherlands)

    Beerlage-de Jong, Nienke; Wentzel, Jobke; Hendrix, Ron; van Gemert-Pijnen, Lisette

    2017-01-01

    Background: Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily

  4. The value of participatory development to support antimicrobial stewardship with a clinical decision support system

    NARCIS (Netherlands)

    Beerlage-de Jong, Nienke; Wentzel, M.J.; Hendrix, Ron; van Gemert-Pijnen, Julia E.W.C.

    Background Current clinical decision support systems (CDSSs) for antimicrobial stewardship programs (ASPs) are guideline- or expert-driven. They are focused on (clinical) content, not on supporting real-time workflow. Thus, CDSSs fail to optimally support prudent antimicrobial prescribing in daily

  5. An Application for Mobile Devices Focused on Clinical Decision Support: Diabetes Mellitus Case

    NARCIS (Netherlands)

    Klein, Lucas Felipe; Rigo, Sandro José; Cazella, Silvio César; Ben, Angela Jornada

    2016-01-01

    Clinical decision-making is performed by health professionals and it is currently connected to the need for manual query for these professionals for clinical guidelines, which are generally formed by large text files, which makes this process very slow and laborious. The development of

  6. Computer Decision Support to Improve Autism Screening and Care in Community Pediatric Clinics

    Science.gov (United States)

    Bauer, Nerissa S.; Sturm, Lynne A.; Carroll, Aaron E.; Downs, Stephen M.

    2013-01-01

    An autism module was added to an existing computer decision support system (CDSS) to facilitate adherence to recommended guidelines for screening for autism spectrum disorders in primary care pediatric clinics. User satisfaction was assessed by survey and informal feedback at monthly meetings between clinical staff and the software team. To assess…

  7. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    Science.gov (United States)

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

  8. Clinical decision making in seizures and status epilepticus.

    Science.gov (United States)

    Teran, Felipe; Harper-Kirksey, Katrina; Jagoda, Andy

    2015-01-01

    Seizures and status epilepticus are frequent neurologic emergencies in the emergency department, accounting for 1% of all emergency department visits. The management of this time-sensitive and potentially life-threatening condition is challenging for both prehospital providers and emergency clinicians. The approach to seizing patients begins with differentiating seizure activity from mimics and follows with identifying potential secondary etiologies, such as alcohol-related seizures. The approach to the patient in status epilepticus and the patient with nonconvulsive status epilepticus constitutes a special clinical challenge. This review summarizes the best available evidence and recommendations regarding diagnosis and resuscitation of the seizing patient in the emergency setting.

  9. BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

    Science.gov (United States)

    Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

    2013-01-01

    De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

  10. Dental patient preferences and choice in clinical decision-making.

    Science.gov (United States)

    Fukai, Kakuhiro; Yoshino, Koichi; Ohyama, Atsushi; Takaesu, Yoshinori

    2012-01-01

    In economics, the concept of utility refers to the strength of customer preference. In health care assessment, the visual analogue scale (VAS), the standard gamble, and the time trade-off are used to measure health state utilities. These utility measurements play a key role in promoting shared decision-making in dental care. Individual preference, however, is complex and dynamic. The purpose of this study was to investigate the relationship between patient preference and educational intervention in the field of dental health. The data were collected by distributing questionnaires to employees of two companies in Japan. Participants were aged 18-65 years and consisted of 111 males and 93 females (204 in total). One company (Group A) had a dental program of annual check-ups and health education in the workplace, while the other company (Group B) had no such program. Statistical analyses were performed with the t-test and Chi-square test. The questionnaire items were designed to determine: (1) oral health-related quality of life, (2) dental health state utilities (using VAS), and (3) time trade-off for regular dental check-ups. The percentage of respondents in both groups who were satisfied with chewing function, appearance of teeth, and social function ranged from 23.1 to 42.4%. There were no significant differences between groups A and B in the VAS of decayed, filled, and missing teeth. The VAS of gum bleeding was 42.8 in Group A and 51.3 in Group B (pdecision-making.

  11. Automation bias: empirical results assessing influencing factors.

    Science.gov (United States)

    Goddard, Kate; Roudsari, Abdul; Wyatt, Jeremy C

    2014-05-01

    To investigate the rate of automation bias - the propensity of people to over rely on automated advice and the factors associated with it. Tested factors were attitudinal - trust and confidence, non-attitudinal - decision support experience and clinical experience, and environmental - task difficulty. The paradigm of simulated decision support advice within a prescribing context was used. The study employed within participant before-after design, whereby 26 UK NHS General Practitioners were shown 20 hypothetical prescribing scenarios with prevalidated correct and incorrect answers - advice was incorrect in 6 scenarios. They were asked to prescribe for each case, followed by being shown simulated advice. Participants were then asked whether they wished to change their prescription, and the post-advice prescription was recorded. Rate of overall decision switching was captured. Automation bias was measured by negative consultations - correct to incorrect prescription switching. Participants changed prescriptions in 22.5% of scenarios. The pre-advice accuracy rate of the clinicians was 50.38%, which improved to 58.27% post-advice. The CDSS improved the decision accuracy in 13.1% of prescribing cases. The rate of automation bias, as measured by decision switches from correct pre-advice, to incorrect post-advice was 5.2% of all cases - a net improvement of 8%. More immediate factors such as trust in the specific CDSS, decision confidence, and task difficulty influenced rate of decision switching. Lower clinical experience was associated with more decision switching. Age, DSS experience and trust in CDSS generally were not significantly associated with decision switching. This study adds to the literature surrounding automation bias in terms of its potential frequency and influencing factors. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  12. Applicability Of A Semi-Automated Clinical Chemistry Analyzer In Determining The Antioxidant Concentrations Of Selected Plants

    OpenAIRE

    Allan L. Hilario; Phylis C. Rio; Geraldine Susan C. Tengco; Danilo M. Menorca

    2017-01-01

    Plants are rich sources of antioxidants that are protective against diseases associated to oxidative stress. There is a need for high throughput screening method that should be useful in determining the antioxidant concentration in plants. Such screening method should significantly simplify and speed up most antioxidant assays. This paper aimed at comparing the applicability of a semi-automated clinical chemistry analyzer Pointe Scientific MI USA with the traditional standard curve method and...

  13. Automated identification of wound information in clinical notes of patients with heart diseases: Developing and validating a natural language processing application.

    Science.gov (United States)

    Topaz, Maxim; Lai, Kenneth; Dowding, Dawn; Lei, Victor J; Zisberg, Anna; Bowles, Kathryn H; Zhou, Li

    2016-12-01

    Electronic health records are being increasingly used by nurses with up to 80% of the health data recorded as free text. However, only a few studies have developed nursing-relevant tools that help busy clinicians to identify information they need at the point of care. This study developed and validated one of the first automated natural language processing applications to extract wound information (wound type, pressure ulcer stage, wound size, anatomic location, and wound treatment) from free text clinical notes. First, two human annotators manually reviewed a purposeful training sample (n=360) and random test sample (n=1100) of clinical notes (including 50% discharge summaries and 50% outpatient notes), identified wound cases, and created a gold standard dataset. We then trained and tested our natural language processing system (known as MTERMS) to process the wound information. Finally, we assessed our automated approach by comparing system-generated findings against the gold standard. We also compared the prevalence of wound cases identified from free-text data with coded diagnoses in the structured data. The testing dataset included 101 notes (9.2%) with wound information. The overall system performance was good (F-measure is a compiled measure of system's accuracy=92.7%), with best results for wound treatment (F-measure=95.7%) and poorest results for wound size (F-measure=81.9%). Only 46.5% of wound notes had a structured code for a wound diagnosis. The natural language processing system achieved good performance on a subset of randomly selected discharge summaries and outpatient notes. In more than half of the wound notes, there were no coded wound diagnoses, which highlight the significance of using natural language processing to enrich clinical decision making. Our future steps will include expansion of the application's information coverage to other relevant wound factors and validation of the model with external data. Copyright © 2016 Elsevier Ltd. All

  14. Human Cognitive Limitations. Broad, Consistent, Clinical Application of Physiological Principles Will Require Decision Support.

    Science.gov (United States)

    Morris, Alan H

    2018-02-01

    Our education system seems to fail to enable clinicians to broadly understand core physiological principles. The emphasis on reductionist science, including "omics" branches of research, has likely contributed to this decrease in understanding. Consequently, clinicians cannot be expected to consistently make clinical decisions linked to best physiological evidence. This is a large-scale problem with multiple determinants, within an even larger clinical decision problem: the failure of clinicians to consistently link their decisions to best evidence. Clinicians, like all human decision-makers, suffer from significant cognitive limitations. Detailed context-sensitive computer protocols can generate personalized medicine instructions that are well matched to individual patient needs over time and can partially resolve this problem.

  15. Automated Text Messaging as an Adjunct to Cognitive Behavioral Therapy for Depression: A Clinical Trial.

    Science.gov (United States)

    Aguilera, Adrian; Bruehlman-Senecal, Emma; Demasi, Orianna; Avila, Patricia

    2017-05-08

    Cognitive Behavioral Therapy (CBT) for depression is efficacious, but effectiveness is limited when implemented in low-income settings due to engagement difficulties including nonadherence with skill-building homework and early discontinuation of treatment. Automated messaging can be used in clinical settings to increase dosage of depression treatment and encourage sustained engagement with psychotherapy. The aim of this study was to test whether a text messaging adjunct (mood monitoring text messages, treatment-related text messages, and a clinician dashboard to display patient data) increases engagement and improves clinical outcomes in a group CBT treatment for depression. Specifically, we aim to assess whether the text messaging adjunct led to an increase in group therapy sessions attended, an increase in duration of therapy attended, and reductions in Patient Health Questionnaire-9 item (PHQ-9) symptoms compared with the control condition of standard group CBT in a sample of low-income Spanish speaking Latino patients. Patients in an outpatient behavioral health clinic were assigned to standard group CBT for depression (control condition; n=40) or the same treatment with the addition of a text messaging adjunct (n=45). The adjunct consisted of a daily mood monitoring message, a daily message reiterating the theme of that week's content, and medication and appointment reminders. Mood data and qualitative responses were sent to a Web-based platform (HealthySMS) for review by the therapist and displayed in session as a tool for teaching CBT skills. Intent-to-treat analyses on therapy attendance during 16 sessions of weekly therapy found that patients assigned to the text messaging adjunct stayed in therapy significantly longer (median of 13.5 weeks before dropping out) than patients assigned to the control condition (median of 3 weeks before dropping out; Wilcoxon-Mann-Whitney z=-2.21, P=.03). Patients assigned to the text messaging adjunct also generally

  16. Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

    Science.gov (United States)

    Dolan, James G

    2010-01-01

    Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

  17. Automated precolumn derivatization procedures in HPLC for biomedical and clinical applications

    NARCIS (Netherlands)

    Wolf, Johannes Hendrik

    1992-01-01

    This thesis describes three automated precolumn derivatization procedures for the analysis of carboxylic group-containing compounds. After derivatization with a suitable label, the derivatives are separated on reversed-phashed HPLC and detected by fluorescence. ... Zie: Summary

  18. Shared decision making in mental health: the importance for current clinical practice.

    Science.gov (United States)

    Alguera-Lara, Victoria; Dowsey, Michelle M; Ride, Jemimah; Kinder, Skye; Castle, David

    2017-12-01

    We reviewed the literature on shared decision making (regarding treatments in psychiatry), with a view to informing our understanding of the decision making process and the barriers that exist in clinical practice. Narrative review of published English-language articles. After culling, 18 relevant articles were included. Themes identified included models of psychiatric care, benefits for patients, and barriers. There is a paucity of published studies specifically related to antipsychotic medications. Shared decision making is a central part of the recovery paradigm and is of increasing importance in mental health service delivery. The field needs to better understand the basis on which decisions are reached regarding psychiatric treatments. Discrete choice experiments might be useful to inform the development of tools to assist shared decision making in psychiatry.

  19. Do educational interventions improve nurses' clinical decision making and judgement? A systematic review.

    Science.gov (United States)

    Thompson, Carl; Stapley, Sally

    2011-07-01

    Despite the growing popularity of decision making in nursing curricula, the effectiveness of educational interventions to improve nursing judgement and decision making is unknown. We sought to synthesise and summarise the comparative evidence for educational interventions to improve nursing judgements and clinical decisions. A systematic review. Electronic databases: Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, CINAHL and PsycINFO, Social Sciences Citation Index, OpenSIGLE conference proceedings and hand searching nursing journals. Studies published since 1960, reporting any educational intervention that aimed to improve nurses' clinical judgements or decision making were included. Studies were assessed for relevance and quality. Data extracted included study design; educational setting; the nature of participants; whether the study was concerned with the clinical application of skills or the application of theory; the type of decision targeted by the intervention (e.g. diagnostic reasoning) and whether the evaluation of the intervention focused on efficacy or effectiveness. A narrative approach to study synthesis was used due to heterogeneity in interventions, study samples, outcomes and settings and incomplete reporting of effect sizes. From 5262 initial citations 24 studies were included in the review. A variety of educational approaches were reported. Study quality and content reporting was generally poor. Pedagogical theories were widely used but use of decision theory (with the exception of subjective expected utility theory implicit in decision analysis) was rare. The effectiveness and efficacy of interventions was mixed. Educational interventions to improve nurses' judgements and decisions are complex and the evidence from comparative studies does little to reduce the uncertainty about 'what works'. Nurse educators need to pay attention to decision, as well as pedagogical, theory in the design of interventions. Study design and

  20. A social-technological epistemology of clinical decision-making as mediated by imaging.

    Science.gov (United States)

    van Baalen, Sophie; Carusi, Annamaria; Sabroe, Ian; Kiely, David G

    2017-10-01

    In recent years there has been growing attention to the epistemology of clinical decision-making, but most studies have taken the individual physicians as the central object of analysis. In this paper we argue that knowing in current medical practice has an inherently social character and that imaging plays a mediating role in these practices. We have analyzed clinical decision-making within a medical expert team involved in diagnosis and treatment of patients with pulmonary hypertension (PH), a rare disease requiring multidisciplinary team involvement in diagnosis and management. Within our field study, we conducted observations, interviews, video tasks, and a panel discussion. Decision-making in the PH clinic involves combining evidence from heterogeneous sources into a cohesive framing of a patient, in which interpretations of the different sources can be made consistent with each other. Because pieces of evidence are generated by people with different expertise and interpretation and adjustments take place in interaction between different experts, we argue that this process is socially distributed. Multidisciplinary team meetings are an important place where information is shared, discussed, interpreted, and adjusted, allowing for a collective way of seeing and a shared language to be developed. We demonstrate this with an example of image processing in the PH service, an instance in which knowledge is distributed over multiple people who play a crucial role in generating an evaluation of right heart function. Finally, we argue that images fulfill a mediating role in distributed knowing in 3 ways: first, as enablers or tools in acquiring information; second, as communication facilitators; and third, as pervasively framing the epistemic domain. With this study of clinical decision-making in diagnosis and treatment of PH, we have shown that clinical decision-making is highly social and mediated by technologies. The epistemology of clinical decision-making needs

  1. GELLO: an object-oriented query and expression language for clinical decision support.

    Science.gov (United States)

    Sordo, Margarita; Ogunyemi, Omolola; Boxwala, Aziz A; Greenes, Robert A

    2003-01-01

    GELLO is a purpose-specific, object-oriented (OO) query and expression language. GELLO is the result of a concerted effort of the Decision Systems Group (DSG) working with the HL7 Clinical Decision Support Technical Committee (CDSTC) to provide the HL7 community with a common format for data encoding and manipulation. GELLO will soon be submitted for ballot to the HL7 CDSTC for consideration as a standard.

  2. Clinical Decision Making and Mental Health Service Use Among Persons With Severe Mental Illness Across Europe.

    Science.gov (United States)

    Cosh, Suzanne; Zenter, Nadja; Ay, Esra-Sultan; Loos, Sabine; Slade, Mike; De Rosa, Corrado; Luciano, Mario; Berecz, Roland; Glaub, Theodora; Munk-Jørgensen, Povl; Krogsgaard Bording, Malene; Rössler, Wulf; Kawohl, Wolfram; Puschner, Bernd

    2017-09-01

    The study explored relationships between preferences for and experiences of clinical decision making (CDM) with service use among persons with severe mental illness. Data from a prospective observational study in six European countries were examined. Associations of baseline staff-rated (N=213) and patient-rated (N=588) preferred and experienced decision making with service use were examined at baseline by using binomial regressions and at 12-month follow-up by using multilevel models. A preference by patients and staff for active patient involvement in decision making, rather than shared or passive decision making, was associated with longer hospital admissions and higher costs at baseline and with increases in admissions over 12 months (p=.043). Low patient-rated satisfaction with an experienced clinical decision was also related to increased costs over the study period (p=.005). A preference for shared decision making may reduce health care costs by reducing inpatient admissions. Patient satisfaction with decisions was a predictor of costs, and clinicians should maximize patient satisfaction with CDM.

  3. Clinical decision making on the use of physical restraint in intensive care units

    Directory of Open Access Journals (Sweden)

    Xinqian Li

    2014-12-01

    Full Text Available Physical restraint is a common nursing intervention in intensive care units and nurses often use it to ensure patients' safety and to prevent unexpected accidents. However, existing literature indicated that the use of physical restraint is a complex one because of inadequate rationales, the negative physical and emotional effects on patients, but the lack of perceived alternatives. This paper is aimed to interpret the clinical decision-making theories related to the use of physical restraint in intensive care units in order to facilitate our understanding on the use of physical restraint and to evaluate the quality of decisions made by nurses. By reviewing the literature, intuition and heuristics are the main decision-making strategies related to the use of physical restraint in intensive care units because the rapid and reflexive nature of intuition and heuristics allow nurses to have a rapid response to urgent and emergent cases. However, it is problematic if nurses simply count their decision-making on experience rather than incorporate research evidence into clinical practice because of inadequate evidence to support the use of physical restraint. Besides that, such a rapid response may lead nurses to make decisions without adequate assessment and thinking and therefore biases and errors may be generated. Therefore, despite the importance of intuition and heuristics in decision-making in acute settings on the use of physical restraint, it is recommended that nurses should incorporate research evidence with their experience to make decisions and adequate assessment before implementing physical restraint is also necessary.

  4. A pilot study of distributed knowledge management and clinical decision support in the cloud.

    Science.gov (United States)

    Dixon, Brian E; Simonaitis, Linas; Goldberg, Howard S; Paterno, Marilyn D; Schaeffer, Molly; Hongsermeier, Tonya; Wright, Adam; Middleton, Blackford

    2013-09-01

    Implement and perform pilot testing of web-based clinical decision support services using a novel framework for creating and managing clinical knowledge in a distributed fashion using the cloud. The pilot sought to (1) develop and test connectivity to an external clinical decision support (CDS) service, (2) assess the exchange of data to and knowledge from the external CDS service, and (3) capture lessons to guide expansion to more practice sites and users. The Clinical Decision Support Consortium created a repository of shared CDS knowledge for managing hypertension, diabetes, and coronary artery disease in a community cloud hosted by Partners HealthCare. A limited data set for primary care patients at a separate health system was securely transmitted to a CDS rules engine hosted in the cloud. Preventive care reminders triggered by the limited data set were returned for display to clinician end users for review and display. During a pilot study, we (1) monitored connectivity and system performance, (2) studied the exchange of data and decision support reminders between the two health systems, and (3) captured lessons. During the six month pilot study, there were 1339 patient encounters in which information was successfully exchanged. Preventive care reminders were displayed during 57% of patient visits, most often reminding physicians to monitor blood pressure for hypertensive patients (29%) and order eye exams for patients with diabetes (28%). Lessons learned were grouped into five themes: performance, governance, semantic interoperability, ongoing adjustments, and usability. Remote, asynchronous cloud-based decision support performed reasonably well, although issues concerning governance, semantic interoperability, and usability remain key challenges for successful adoption and use of cloud-based CDS that will require collaboration between biomedical informatics and computer science disciplines. Decision support in the cloud is feasible and may be a reasonable

  5. Newly graduated nurses' use of knowledge sources in clinical decision-making

    DEFF Research Database (Denmark)

    Voldbjerg, Siri Lygum; Grønkjaer, Mette; Wiechula, Rick

    2017-01-01

    AIMS AND OBJECTIVES: To explore which knowledge sources newly graduated nurses' use in clinical decision-making and why and how they are used. BACKGROUND: In spite of an increased educational focus on skills and competencies within evidence based practice newly graduated nurses' ability to use...... approaches to strengthen the knowledgebase used in clinical decision-making. DESIGN AND METHODS: Ethnographic study using participant-observation and individual semi-structured interviews of nine Danish newly graduated nurses in medical and surgical hospital settings. RESULTS: Newly graduates use...... in clinical decision-making. If newly graduates are to be supported in an articulate and reflective use of a variety of sources, they have to be allocated to experienced nurses who model a reflective, articulate and balanced use of knowledge sources. This article is protected by copyright. All rights reserved....

  6. Improving Breast Cancer Surgical Treatment Decision Making: The iCanDecide Randomized Clinical Trial.

    Science.gov (United States)

    Hawley, Sarah T; Li, Yun; An, Lawrence C; Resnicow, Kenneth; Janz, Nancy K; Sabel, Michael S; Ward, Kevin C; Fagerlin, Angela; Morrow, Monica; Jagsi, Reshma; Hofer, Timothy P; Katz, Steven J

    2018-03-01

    Purpose This study was conducted to determine the effect of iCanDecide, an interactive and tailored breast cancer treatment decision tool, on the rate of high-quality patient decisions-both informed and values concordant-regarding locoregional breast cancer treatment and on patient appraisal of decision making. Methods We conducted a randomized clinical trial of newly diagnosed patients with early-stage breast cancer making locoregional treatment decisions. From 22 surgical practices, 537 patients were recruited and randomly assigned online to the iCanDecide interactive and tailored Web site (intervention) or the iCanDecide static Web site (control). Participants completed a baseline survey and were mailed a follow-up survey 4 to 5 weeks after enrollment to assess the primary outcome of a high-quality decision, which consisted of two components, high knowledge and values-concordant treatment, and secondary outcomes (decision preparation, deliberation, and subjective decision quality). Results Patients in the intervention arm had higher odds of making a high-quality decision than did those in the control arm (odds ratio, 2.00; 95% CI, 1.37 to 2.92; P = .0004), which was driven primarily by differences in the rates of high knowledge between groups. The majority of patients in both arms made values-concordant treatment decisions (78.6% in the intervention arm and 81.4% in the control arm). More patients in the intervention arm had high decision preparation (estimate, 0.18; 95% CI, 0.02 to 0.34; P = .027), but there were no significant differences in the other decision appraisal outcomes. The effect of the intervention was similar for women who were leaning strongly toward a treatment option at enrollment compared with those who were not. Conclusion The tailored and interactive iCanDecide Web site, which focused on knowledge building and values clarification, positively affected high-quality decisions largely by improving knowledge compared with static online

  7. Automated, simple, and efficient influenza RNA extraction from clinical respiratory swabs using TruTip and epMotion.

    Science.gov (United States)

    Griesemer, Sara B; Holmberg, Rebecca; Cooney, Christopher G; Thakore, Nitu; Gindlesperger, Alissa; Knickerbocker, Christopher; Chandler, Darrell P; St George, Kirsten

    2013-09-01

    Rapid, simple and efficient influenza RNA purification from clinical samples is essential for sensitive molecular detection of influenza infection. Automation of the TruTip extraction method can increase sample throughput while maintaining performance. To automate TruTip influenza RNA extraction using an Eppendorf epMotion robotic liquid handler, and to compare its performance to the bioMerieux easyMAG and Qiagen QIAcube instruments. Extraction efficacy and reproducibility of the automated TruTip/epMotion protocol was assessed from influenza-negative respiratory samples spiked with influenza A and B viruses. Clinical extraction performance from 170 influenza A and B-positive respiratory swabs was also evaluated and compared using influenza A and B real-time RT-PCR assays. TruTip/epMotion extraction efficacy was 100% in influenza virus-spiked samples with at least 745 influenza A and 370 influenza B input gene copies per extraction, and exhibited high reproducibility over four log10 concentrations of virus (extraction were also positive following TruTip extraction. Overall Ct value differences obtained between TruTip/epMotion and easyMAG/QIAcube clinical extracts ranged from 1.24 to 1.91. Pairwise comparisons of Ct values showed a high correlation of the TruTip/epMotion protocol to the other methods (R2>0.90). The automated TruTip/epMotion protocol is a simple and rapid extraction method that reproducibly purifies influenza RNA from respiratory swabs, with comparable efficacy and efficiency to both the easyMAG and QIAcube instruments. Copyright © 2013 Elsevier B.V. All rights reserved.

  8. Clinical decision-making: predictors of patient participation in nursing care.

    Science.gov (United States)

    Florin, Jan; Ehrenberg, Anna; Ehnfors, Margareta

    2008-11-01

    To investigate predictors of patients' preferences for participation in clinical decision-making in inpatient nursing care. Patient participation in decision-making in nursing care is regarded as a prerequisite for good clinical practice regarding the person's autonomy and integrity. A cross-sectional survey of 428 persons, newly discharged from inpatient care. The survey was conducted using the Control Preference Scale. Multiple logistic regression analysis was used for testing the association of patient characteristics with preferences for participation. Patients, in general, preferred adopting a passive role. However, predictors for adopting an active participatory role were the patient's gender (odds ratio = 1.8), education (odds ratio = 2.2), living condition (odds ratio = 1.8) and occupational status (odds ratio = 2.0). A probability of 53% was estimated, which female senior citizens with at least a high school degree and who lived alone would prefer an active role in clinical decision-making. At the same time, a working cohabiting male with less than a high school degree had a probability of 8% for active participation in clinical decision making in nursing care. Patient preferences for participation differed considerably and are best elicited by assessment of the individual patient. Relevance to clinical practice. The nurses have a professional responsibility to act in such a way that patients can participate and make decisions according to their own values from an informed position. Access to knowledge of patients'basic assumptions and preferences for participation is of great value for nurses in the care process. There is a need for nurses to use structured methods and tools for eliciting individual patient preferences regarding participation in clinical decision-making.

  9. Sensitivity of a Clinical Decision Rule and Early Computed Tomography in Aneurysmal Subarachnoid Hemorrhage

    Directory of Open Access Journals (Sweden)

    Dustin G. Mark

    2015-10-01

    Full Text Available Introduction: Application of a clinical decision rule for subarachnoid hemorrhage, in combination with cranial computed tomography (CT performed within six hours of ictus (early cranial CT, may be able to reasonably exclude a diagnosis of aneurysmal subarachnoid hemorrhage (aSAH. This study’s objective was to examine the sensitivity of both early cranial CT and a previously validated clinical decision rule among emergency department (ED patients with aSAH and a normal mental status. Methods: Patients were evaluated in the 21 EDs of an integrated health delivery system between January 2007 and June 2013. We identified by chart review a retrospective cohort of patients diagnosed with aSAH in the setting of a normal mental status and performance of early cranial CT. Variables comprising the SAH clinical decision rule (age >40, presence of neck pain or stiffness, headache onset with exertion, loss of consciousness at headache onset were abstracted from the chart and assessed for inter-rater reliability. Results: One hundred fifty-five patients with aSAH met study inclusion criteria. The sensitivity of early cranial CT was 95.5% (95% CI [90.9-98.2]. The sensitivity of the SAH clinical decision rule was also 95.5% (95% CI [90.9-98.2]. Since all false negative cases for each diagnostic modality were mutually independent, the combined use of both early cranial CT and the clinical decision rule improved sensitivity to 100% (95% CI [97.6-100.0]. Conclusion: Neither early cranial CT nor the SAH clinical decision rule demonstrated ideal sensitivity for aSAH in this retrospective cohort. However, the combination of both strategies might optimize sensitivity for this life-threatening disease.

  10. Performance evaluation of enzyme immunoassay for voriconazole therapeutic drug monitoring with automated clinical chemistry analyzers

    Directory of Open Access Journals (Sweden)

    Yongbum Jeon

    2017-08-01

    Full Text Available Objective: Voriconazole is a triazole antifungal developed for the treatment of fungal infectious disease, and the clinical utility of its therapeutic drug monitoring has been evaluated. Recently, a new assay for analyzing the serum voriconazole concentration with an automated clinical chemistry analyzer was developed. We evaluated the performance of the new assay based on standardized protocols. Methods: The analytical performance of the assay was evaluated according to its precision, trueness by recovery, limit of quantitation, linearity, and correlation with results from liquid chromatography-tandem mass spectrometry (LC-MS/MS. The evaluation was performed with the same protocol on two different routine chemistry analyzers. All evaluations were performed according to CLSI Guidelines EP15, EP17, EP6, and EP9 [1–4]. Results: Coefficients of variation for within-run and between-day imprecision were 3.2–5.1% and 1.5–3.0%, respectively, on the two different analyzers for pooled serum samples. The recovery rates were in the range of 95.4–102.2%. The limit of blank was 0.0049 μg/mL, and the limit of detection of the samples was 0.0266–0.0376 μg/mL. The percent recovery at three LoQ levels were 67.9–74.6% for 0.50 μg/mL, 75.5–80.2% for 0.60 μg/mL, and 89.9–96.6% for 0.70 μg/mL. A linear relationship was demonstrated between 0.5 μg/mL and 16.0 μg/mL (R2=0.9995–0.9998. The assay correlated well with LC-MS/MS results (R2=0.9739–0.9828. Conclusions: The assay showed acceptable precision, trueness, linearity, and limit of quantification, and correlated well with LC-MS/MS. Therefore, its analytical performance is satisfactory for monitoring the drug concentration of voriconazole. Keywords: Voriconazole, Antifungal agents, Therapeutic drug monitoring

  11. Performance evaluation of enzyme immunoassay for voriconazole therapeutic drug monitoring with automated clinical chemistry analyzers.

    Science.gov (United States)

    Jeon, Yongbum; Han, Minje; Han, Eun Young; Lee, Kyunghoon; Song, Junghan; Song, Sang Hoon

    2017-08-01

    Voriconazole is a triazole antifungal developed for the treatment of fungal infectious disease, and the clinical utility of its therapeutic drug monitoring has been evaluated. Recently, a new assay for analyzing the serum voriconazole concentration with an automated clinical chemistry analyzer was developed. We evaluated the performance of the new assay based on standardized protocols. The analytical performance of the assay was evaluated according to its precision, trueness by recovery, limit of quantitation, linearity, and correlation with results from liquid chromatography-tandem mass spectrometry (LC-MS/MS). The evaluation was performed with the same protocol on two different routine chemistry analyzers. All evaluations were performed according to CLSI Guidelines EP15, EP17, EP6, and EP9 [1-4]. Coefficients of variation for within-run and between-day imprecision were 3.2-5.1% and 1.5-3.0%, respectively, on the two different analyzers for pooled serum samples. The recovery rates were in the range of 95.4-102.2%. The limit of blank was 0.0049 μg/mL, and the limit of detection of the samples was 0.0266-0.0376 μg/mL. The percent recovery at three LoQ levels were 67.9-74.6% for 0.50 μg/mL, 75.5-80.2% for 0.60 μg/mL, and 89.9-96.6% for 0.70 μg/mL. A linear relationship was demonstrated between 0.5 μg/mL and 16.0 μg/mL ( R 2 =0.9995-0.9998). The assay correlated well with LC-MS/MS results ( R 2 =0.9739-0.9828). The assay showed acceptable precision, trueness, linearity, and limit of quantification, and correlated well with LC-MS/MS. Therefore, its analytical performance is satisfactory for monitoring the drug concentration of voriconazole.

  12. Big Data as a Driver for Clinical Decision Support Systems: A Learning Health Systems Perspective

    Directory of Open Access Journals (Sweden)

    Arianna Dagliati

    2018-05-01

    Full Text Available Big data technologies are nowadays providing health care with powerful instruments to gather and analyze large volumes of heterogeneous data collected for different purposes, including clinical care, administration, and research. This makes possible to design IT infrastructures that favor the implementation of the so-called “Learning Healthcare System Cycle,” where healthcare practice and research are part of a unique and synergic process. In this paper we highlight how “Big Data enabled” integrated data collections may support clinical decision-making together with biomedical research. Two effective implementations are reported, concerning decision support in Diabetes and in Inherited Arrhythmogenic Diseases.

  13. Potential Impact on Clinical Decision Making via a Genome-Wide Expression Profiling: A Case Report

    Directory of Open Access Journals (Sweden)

    Hyun Kim

    2016-11-01

    Full Text Available Management of men with prostate cancer is fraught with uncertainty as physicians and patients balance efficacy with potential toxicity and diminished quality of life. Utilization of genomics as a prognostic biomarker has improved the informed decision-making process by enabling more rationale treatment choices. Recently investigations have begun to determine whether genomic information from tumor transcriptome data can be used to impact clinical decision-making beyond prognosis. Here we discuss the potential of genomics to alter management of a patient who presented with high-risk prostate adenocarcinoma. We suggest that this information help selecting patients for advanced imaging, chemotherapies, or clinical trial.

  14. Managed care and clinical decision-making in child and adolescent behavioral health: provider perceptions.

    Science.gov (United States)

    Yanos, Philip T; Garcia, Christine I; Hansell, Stephen; Rosato, Mark G; Minsky, Shula

    2003-03-01

    This study investigated how managed care affects clinical decision-making in a behavioral health care system. Providers serving children and adolescents under both managed and unmanaged care (n = 28) were interviewed about their awareness of differences between the benefit arrangements, how benefits affect clinical decision-making, outcomes and quality of care; and satisfaction with care. Quantitative and qualitative findings indicated that providers saw both advantages and disadvantages to managed care. Although most providers recognized the advantages of managed care in increasing efficiency, many were concerned that administrative pressures associated with managed care compromise service quality.

  15. Computerized clinical decision support systems for chronic disease management: a decision-maker-researcher partnership systematic review.

    Science.gov (United States)

    Roshanov, Pavel S; Misra, Shikha; Gerstein, Hertzel C; Garg, Amit X; Sebaldt, Rolf J; Mackay, Jean A; Weise-Kelly, Lorraine; Navarro, Tamara; Wilczynski, Nancy L; Haynes, R Brian

    2011-08-03

    The use of computerized clinical decision support systems (CCDSSs) may improve chronic disease management, which requires recurrent visits to multiple health professionals, ongoing disease and treatment monitoring, and patient behavior modification. The objective of this review was to determine if CCDSSs improve the processes of chronic care (such as diagnosis, treatment, and monitoring of disease) and associated patient outcomes (such as effects on biomarkers and clinical exacerbations). We conducted a decision-maker-researcher partnership systematic review. We searched MEDLINE, EMBASE, Ovid's EBM Reviews database, Inspec, and reference lists for potentially eligible articles published up to January 2010. We included randomized controlled trials that compared the use of CCDSSs to usual practice or non-CCDSS controls. Trials were eligible if at least one component of the CCDSS was designed to support chronic disease management. We considered studies 'positive' if they showed a statistically significant improvement in at least 50% of relevant outcomes. Of 55 included trials, 87% (n = 48) measured system impact on the process of care and 52% (n = 25) of those demonstrated statistically significant improvements. Sixty-five percent (36/55) of trials measured impact on, typically, non-major (surrogate) patient outcomes, and 31% (n = 11) of those demonstrated benefits. Factors of interest to decision makers, such as cost, user satisfaction, system interface and feature sets, unique design and deployment characteristics, and effects on user workflow were rarely investigated or reported. A small majority (just over half) of CCDSSs improved care processes in chronic disease management and some improved patient health. Policy makers, healthcare administrators, and practitioners should be aware that the evidence of CCDSS effectiveness is limited, especially with respect to the small number and size of studies measuring patient outcomes.

  16. Postnatal Psychosocial Assessment and Clinical Decision-Making, a Descriptive Study.

    Science.gov (United States)

    Sims, Deborah; Fowler, Cathrine

    2018-05-18

    The aim of this study is to describe experienced child and family health nurses' clinical decision-making during a postnatal psychosocial assessment. Maternal emotional wellbeing in the postnatal year optimises parenting and promotes infant development. Psychosocial assessment potentially enables early intervention and reduces the risk of a mental disorder occurring during this time of change. Assessment accuracy, and the interventions used are determined by the standard of nursing decision-making. A qualitative methodology was employed to explore decision-making behaviour when conducting a postnatal psychosocial assessment. This study was conducted in an Australian early parenting organisation. Twelve experienced child and family health nurses were interviewed. A detailed description of a postnatal psychosocial assessment process was obtained using a critical incident technique. Template analysis was used to determine the information domains the nurses accessed, and content analysis was used to determine the nurses' thinking strategies, to make clinical decisions from this assessment. The nurses described 24 domains of information and used 17 thinking strategies, in a variety of combinations. The four information domains most commonly used were parenting, assessment tools, women-determined issues and sleep. The seven thinking strategies most commonly used were searching for information, forming relationships between the information, recognising a pattern, drawing a conclusion, setting priorities, providing explanations for the information and judging the value of the information. The variety and complexity of the clinical decision-making involved in postnatal psychosocial assessment confirms that the nurses use information appropriately and within their scope of nursing practice. The standard of clinical decision-making determines the results of the assessment and the optimal access to care. Knowledge of the information domains and the decision-making strategies

  17. What is a “good” treatment decision?: Decisional control, knowledge, treatment decision-making, and quality of life in men with clinically localized prostate cancer

    Science.gov (United States)

    Orom, Heather; Biddle, Caitlin; Underwood, Willie; Nelson, Christian J.; Homish, D. Lynn

    2016-01-01

    Objective We explored whether active patient involvement in decision making and greater patient knowledge are associated with better treatment decision making experiences and better quality of life (QOL) among men with clinically localized prostate cancer. Localized prostate cancer treatment decision-making is an advantageous model for studying patient treatment decision-making dynamics as there are multiple treatment options and a lack of empirical evidence to recommend one over the other; consequently, it is recommended that patients be fully involved in making the decision. Methods Men with newly diagnosed clinically localized prostate cancer (N=1529) completed measures of decisional control, prostate cancer knowledge, and their decision-making experience (decisional conflict, and decision-making satisfaction and difficulty) shortly after they made their treatment decision. Prostate cancer-specific QOL was assessed 6-months after treatment. Results More active involvement in decision making and greater knowledge were associated with lower decisional conflict and higher decision-making satisfaction, but greater decision-making difficulty. An interaction between decisional control and knowledge revealed that greater knowledge was only associated with greater difficulty for men actively involved in making the decision (67% of sample). Greater knowledge, but not decisional control predicted better QOL 6-months post-treatment. Conclusion Although men who are actively involved in decision making and more knowledgeable may make more informed decisions, they could benefit from decisional support (e.g., decision-making aids, emotional support from providers, strategies for reducing emotional distress) to make the process easier. Men who were more knowledgeable about prostate cancer and treatment side effects at the time they made their treatment decision may have appraised their QOL as higher because they had realistic expectations about side effects. PMID:26957566

  18. Standardized Ki67 Diagnostics Using Automated Scoring--Clinical Validation in the GeparTrio Breast Cancer Study.

    Science.gov (United States)

    Klauschen, Frederick; Wienert, Stephan; Schmitt, Wolfgang D; Loibl, Sibylle; Gerber, Bernd; Blohmer, Jens-Uwe; Huober, Jens; Rüdiger, Thomas; Erbstößer, Erhard; Mehta, Keyur; Lederer, Bianca; Dietel, Manfred; Denkert, Carsten; von Minckwitz, Gunter

    2015-08-15

    Scoring proliferation through Ki67 immunohistochemistry is an important component in predicting therapy response to chemotherapy in patients with breast cancer. However, recent studies have cast doubt on the reliability of "visual" Ki67 scoring in the multicenter setting, particularly in the lower, yet clinically important, proliferation range. Therefore, an accurate and standardized Ki67 scoring is pivotal both in routine diagnostics and larger multicenter studies. We validated a novel fully automated Ki67 scoring approach that relies on only minimal a priori knowledge on cell properties and requires no training data for calibration. We applied our approach to 1,082 breast cancer samples from the neoadjuvant GeparTrio trial and compared the performance of automated and manual Ki67 scoring. The three groups of autoKi67 as defined by low (≤ 15%), medium (15.1%-35%), and high (>35%) automated scores showed pCR rates of 5.8%, 16.9%, and 29.5%, respectively. AutoKi67 was significantly linked to prognosis with overall and progression-free survival P values P(OS) cancer that correlated with clinical endpoints and is deployable in routine diagnostics. It may thus help to solve recently reported reliability concerns in Ki67 diagnostics. ©2014 American Association for Cancer Research.

  19. Ethically-based clinical decision-making in physical therapy: process and issues.

    Science.gov (United States)

    Finch, Elspeth; Geddes, E Lynne; Larin, Hélène

    2005-01-01

    The identification and consideration of relevant ethical issues in clinical decision-making, and the education of health care professionals (HCPs) in these skills are key factors in providing quality health care. This qualitative study explores the way in which physical therapists (PTs) integrate ethical issues into clinical practice decisions and identifies ethical themes used by PTs. A purposive sample of eight PTs was asked to describe a recent ethically-based clinical decision. Transcribed interviews were coded and themes identified related to the following categories: 1) the integration of ethical issues in the clinical decision-making process, 2) patient welfare, 3) professional ethos of the PT, and 4) health care economics and business practices. Participants readily described clinical situations involving ethical issues but rarely identified specific conflicting ethical issues in their description. Ethical dilemmas were more frequently resolved when there were fewer emotional sequelae associated with the dilemma, and the PT had a clear understanding of professional ethos, valued patient autonomy, and explored a variety of alternative actions before implementing one. HCP students need to develop a clear professional ethos and an increased understanding of the economic factors that will present ethical issues in practice.

  20. Many faces of rationality: Implications of the great rationality debate for clinical decision-making.

    Science.gov (United States)

    Djulbegovic, Benjamin; Elqayam, Shira

    2017-10-01

    Given that more than 30% of healthcare costs are wasted on inappropriate care, suboptimal care is increasingly connected to the quality of medical decisions. It has been argued that personal decisions are the leading cause of death, and 80% of healthcare expenditures result from physicians' decisions. Therefore, improving healthcare necessitates improving medical decisions, ie, making decisions (more) rational. Drawing on writings from The Great Rationality Debate from the fields of philosophy, economics, and psychology, we identify core ingredients of rationality commonly encountered across various theoretical models. Rationality is typically classified under umbrella of normative (addressing the question how people "should" or "ought to" make their decisions) and descriptive theories of decision-making (which portray how people actually make their decisions). Normative theories of rational thought of relevance to medicine include epistemic theories that direct practice of evidence-based medicine and expected utility theory, which provides the basis for widely used clinical decision analyses. Descriptive theories of rationality of direct relevance to medical decision-making include bounded rationality, argumentative theory of reasoning, adaptive rationality, dual processing model of rationality, regret-based rationality, pragmatic/substantive rationality, and meta-rationality. For the first time, we provide a review of wide range of theories and models of rationality. We showed that what is "rational" behaviour under one rationality theory may be irrational under the other theory. We also showed that context is of paramount importance to rationality and that no one model of rationality can possibly fit all contexts. We suggest that in context-poor situations, such as policy decision-making, normative theories based on expected utility informed by best research evidence may provide the optimal approach to medical decision-making, whereas in the context

  1. Applicability Of A Semi-Automated Clinical Chemistry Analyzer In Determining The Antioxidant Concentrations Of Selected Plants

    Directory of Open Access Journals (Sweden)

    Allan L. Hilario

    2017-07-01

    Full Text Available Plants are rich sources of antioxidants that are protective against diseases associated to oxidative stress. There is a need for high throughput screening method that should be useful in determining the antioxidant concentration in plants. Such screening method should significantly simplify and speed up most antioxidant assays. This paper aimed at comparing the applicability of a semi-automated clinical chemistry analyzer Pointe Scientific MI USA with the traditional standard curve method and using a Vis spectrophotometer in performing the DPPH assay for antioxidant screening. Samples of crude aqueous leaf extract of kulitis Amaranthus viridis Linn and chayote Sechium edule Linn were screened for the Total Antioxidant Concentration TAC using the two methods. Results presented in mean SD amp956gdl were compared using unpaired Students t-test P0.05. All runs were done in triplicates. The mean TAC of A. viridis was 646.0 45.5 amp956gdl using the clinical chemistry analyzer and 581.9 19.4 amp956gdl using the standard curve-spectrophotometer. On the other hand the mean TAC of S. edule was 660.2 35.9 amp956gdl using the semi-automated clinical chemistry analyzer and 672.3 20.9 amp956gdl using the spectrophotometer. No significant differences were observed between the readings of the two methods for A. viridis P0.05 and S. edible P0.05. This implies that the clinical chemistry analyzer can be an alternative method in conducting the DPPH assay to determine the TAC in plants. This study presented the applicability of a semi-automated clinical chemistry analyzer in performing the DPPH assay. Further validation can be conducted by performing other antioxidant assays using this equipment.

  2. Deepening the quality of clinical reasoning and decision-making in rural hospital nursing practice.

    Science.gov (United States)

    Sedgwick, M G; Grigg, L; Dersch, S

    2014-01-01

    Rural acute care nursing requires an extensive breadth and depth of knowledge as well as the ability to quickly reason through problems in order to make sound clinical decisions. This reasoning often occurs within an environment that has minimal medical or ancillary support. Registered nurses (RN) new to rural nursing, and employers, have raised concerns about patient safety while new nurses make the transition into rural practice. In addition, feeling unprepared for the rigors of rural hospital nursing practice is a central issue influencing RN recruitment and retention. Understanding how rural RNs reason is a key element for identifying professional development needs and may support recruitment and retention of skilled rural nurses. The purpose of this study was to explore how rural RNs reason through clinical problems as well as to assess the quality of such reasoning. This study used a non-traditional approach for data collection. Fifteen rural acute care nurses with varying years of experience working in southern Alberta, Canada, were observed while they provided care to patients of varying acuity within a simulated rural setting. Following the simulation, semi-structured interviews were conducted using a substantive approach to critical thinking. Findings revealed that the ability to engage in deep clinical reasoning varied considerably among participants despite being given the same information under the same circumstances. Furthermore, the number of years of experience did not seem to be directly linked to the ability to engage in sound clinical reasoning. Novice nurses, however, did rely heavily on others in their decision making in order to ensure they were making the right decision. Hence, their relationships with other staff members influenced their ability to engage in clinical reasoning and decision making. In situations where the patient's condition was deteriorating quickly, regardless of years of experience, all of the participants depended on

  3. Enhancing decision making about participation in cancer clinical trials: development of a question prompt list

    Science.gov (United States)

    Brown, Richard F.; Shuk, Elyse; Leighl, Natasha; Butow, Phyllis; Ostroff, Jamie; Edgerson, Shawna; Tattersall, Martin

    2016-01-01

    Purpose Slow accrual to cancer clinical trials impedes the progress of effective new cancer treatments. Poor physician–patient communication has been identified as a key contributor to low trial accrual. Question prompt lists (QPLs) have demonstrated a significant promise in facilitating communication in general, surgical, and palliative oncology settings. These simple patient interventions have not been tested in the oncology clinical trial setting. We aimed to develop a targeted QPL for clinical trials (QPL-CT). Method Lung, breast, and prostate cancer patients who either had (trial experienced) or had not (trial naive) participated in a clinical trial were invited to join focus groups to help develop and explore the acceptability of a QPL-CT. Focus groups were audio-recorded and transcribed. A research team, including a qualitative data expert, analyzed these data to explore patients’ decision-making processes and views about the utility of the QPL-CT prompt to aid in trial decision making. Results Decision making was influenced by the outcome of patients’ comparative assessment of perceived risks versus benefits of a trial, and the level of trust patients had in their doctors’ recommendation about the trial. Severity of a patient’s disease influenced trial decision making only for trial-naive patients. Conclusion Although patients were likely to prefer a paternalistic decision-making style, they expressed valuation of the QPL as an aid to decision making. QPL-CT utility extended beyond the actual consultation to include roles both before and after the clinical trial discussion. PMID:20593202

  4. Variation in clinical decision-making for induction of labour: a qualitative study.

    Science.gov (United States)

    Nippita, Tanya A; Porter, Maree; Seeho, Sean K; Morris, Jonathan M; Roberts, Christine L

    2017-09-22

    Unexplained variation in induction of labour (IOL) rates exist between hospitals, even after accounting for casemix and hospital differences. We aimed to explore factors that influence clinical decision-making for IOL that may be contributing to the variation in IOL rates between hospitals. We undertook a qualitative study involving semi-structured, audio-recorded interviews with obstetricians and midwives. Using purposive sampling, participants known to have diverse opinions on IOL were selected from ten Australian maternity hospitals (based on differences in hospital IOL rate, size, location and case-mix complexities). Transcripts were indexed, coded, and analysed using the Framework Approach to identify main themes and subthemes. Forty-five participants were interviewed (21 midwives, 24 obstetric medical staff). Variations in decision-making for IOL were based on the obstetrician's perception of medical risk in the pregnancy (influenced by the obstetrician's personality and knowledge), their care relationship with the woman, how they involved the woman in decision-making, and resource availability. The role of a 'gatekeeper' in the procedural aspects of arranging an IOL also influenced decision-making. There was wide variation in the clinical decision-making practices of obstetricians and less accountability for decision-making in hospitals with a high IOL rate, with the converse occurring in hospitals with low IOL rates. Improved communication, standardised risk assessment and accountability for IOL offer potential for reducing variation in hospital IOL rates.

  5. Incorporating uncertainty regarding applicability of evidence from meta-analyses into clinical decision making.

    Science.gov (United States)

    Kriston, Levente; Meister, Ramona

    2014-03-01

    Judging applicability (relevance) of meta-analytical findings to particular clinical decision-making situations remains challenging. We aimed to describe an evidence synthesis method that accounts for possible uncertainty regarding applicability of the evidence. We conceptualized uncertainty regarding applicability of the meta-analytical estimates to a decision-making situation as the result of uncertainty regarding applicability of the findings of the trials that were included in the meta-analysis. This trial-level applicability uncertainty can be directly assessed by the decision maker and allows for the definition of trial inclusion probabilities, which can be used to perform a probabilistic meta-analysis with unequal probability resampling of trials (adaptive meta-analysis). A case study with several fictitious decision-making scenarios was performed to demonstrate the method in practice. We present options to elicit trial inclusion probabilities and perform the calculations. The result of an adaptive meta-analysis is a frequency distribution of the estimated parameters from traditional meta-analysis that provides individually tailored information according to the specific needs and uncertainty of the decision maker. The proposed method offers a direct and formalized combination of research evidence with individual clinical expertise and may aid clinicians in specific decision-making situations. Copyright © 2014 Elsevier Inc. All rights reserved.

  6. Science and intuition: do both have a place in clinical decision making?

    Science.gov (United States)

    Pearson, Helen

    Intuition is widely used in clinical decision making yet its use is underestimated compared to scientific decision-making methods. Information processing is used within scientific decision making and is methodical and analytical, whereas intuition relies more on a practitioner's perception. Intuition is an unconscious process and may be referred to as a 'sixth sense', 'hunch' or 'gut feeling'. It is not underpinned by valid and reliable measures. Expert health professionals use a rapid, automatic process to recognise familiar problems instantly. Intuition could therefore involve pattern recognition, where experts draw on experiences, so could be perceived as a cognitive skill rather than a perception or knowing without knowing how. The NHS places great importance on evidence-based practice but intuition is seemingly becoming an acceptable way of thinking and knowing in clinical decision making. Recognising nursing as an art allows intuition to be used and the environment or situation to be interpreted to help inform decision making. Intuition can be used in conjunction with evidence-based practice and to achieve good outcomes and deserves to be acknowledged within clinical practice.

  7. Developing an Interactive Data Visualization Tool to Assess the Impact of Decision Support on Clinical Operations.

    Science.gov (United States)

    Huber, Timothy C; Krishnaraj, Arun; Monaghan, Dayna; Gaskin, Cree M

    2018-05-18

    Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.

  8. A system dynamics model of clinical decision thresholds for the detection of developmental-behavioral disorders

    Directory of Open Access Journals (Sweden)

    R. Christopher Sheldrick

    2016-11-01

    Full Text Available Abstract Background Clinical decision-making has been conceptualized as a sequence of two separate processes: assessment of patients’ functioning and application of a decision threshold to determine whether the evidence is sufficient to justify a given decision. A range of factors, including use of evidence-based screening instruments, has the potential to influence either or both processes. However, implementation studies seldom specify or assess the mechanism by which screening is hypothesized to influence clinical decision-making, thus limiting their ability to address unexpected findings regarding clinicians’ behavior. Building on prior theory and empirical evidence, we created a system dynamics (SD model of how physicians’ clinical decisions are influenced by their assessments of patients and by factors that may influence decision thresholds, such as knowledge of past patient outcomes. Using developmental-behavioral disorders as a case example, we then explore how referral decisions may be influenced by changes in context. Specifically, we compare predictions from the SD model to published implementation trials of evidence-based screening to understand physicians’ management of positive screening results and changes in referral rates. We also conduct virtual experiments regarding the influence of a variety of interventions that may influence physicians’ thresholds, including improved access to co-located mental health care and improved feedback systems regarding patient outcomes. Results Results of the SD model were consistent with recent implementation trials. For example, the SD model suggests that if screening improves physicians’ accuracy of assessment without also influencing decision thresholds, then a significant proportion of children with positive screens will not be referred and the effect of screening implementation on referral rates will be modest—results that are consistent with a large proportion of published

  9. Clinical decision making in cancer care: a review of current and future roles of patient age.

    Science.gov (United States)

    Tranvåg, Eirik Joakim; Norheim, Ole Frithjof; Ottersen, Trygve

    2018-05-09

    Patient age is among the most controversial patient characteristics in clinical decision making. In personalized cancer medicine it is important to understand how individual characteristics do affect practice and how to appropriately incorporate such factors into decision making. Some argue that using age in decision making is unethical, and how patient age should guide cancer care is unsettled. This article provides an overview of the use of age in clinical decision making and discusses how age can be relevant in the context of personalized medicine. We conducted a scoping review, searching Pubmed for English references published between 1985 and May 2017. References concerning cancer, with patients above the age of 18 and that discussed age in relation to diagnostic or treatment decisions were included. References that were non-medical or concerning patients below the age of 18, and references that were case reports, ongoing studies or opinion pieces were excluded. Additional references were collected through snowballing and from selected reports, guidelines and articles. Three hundred and forty-seven relevant references were identified. Patient age can have many and diverse roles in clinical decision making: Contextual roles linked to access (age influences how fast patients are referred to specialized care) and incidence (association between increasing age and increasing incidence rates for cancer); patient-relevant roles linked to physiology (age-related changes in drug metabolism) and comorbidity (association between increasing age and increasing number of comorbidities); and roles related to interventions, such as treatment (older patients receive substandard care) and outcome (survival varies by age). Patient age is integrated into cancer care decision making in a range of ways that makes it difficult to claim age-neutrality. Acknowledging this and being more transparent about the use of age in decision making are likely to promote better clinical decisions

  10. Professional autonomy in 21st century healthcare: Nurses' accounts of clinical decision-making

    DEFF Research Database (Denmark)

    Traynor, Michael; Boland, Maggie; Buus, Niels

    2010-01-01

    Autonomy in decision-making has traditionally been described as a feature of professional work, however the work of healthcare professionals has been seen as steadily encroached upon by State and managerialist forces. Nursing has faced particular problems in establishing itself as a credible....... The study uses accounts of decision-making to gain insight into contemporary professional nursing. The study also aims to explore the usefulness of a theory of professional work set out by Jamous and Peloille (1970). The analysis draws on notions of interpretive repertoires and elements of narrative...... analysis. We identified two interpretive repertoires: 'clinical judgement' which was used to describe the different grounds for making judgements; and 'decision-making' which was used to describe organisational circumstances influencing decision-making. Jamous and Peloille's theory proved useful...

  11. Mobile clinical decision support systems and applications: a literature and commercial review.

    Science.gov (United States)

    Martínez-Pérez, Borja; de la Torre-Díez, Isabel; López-Coronado, Miguel; Sainz-de-Abajo, Beatriz; Robles, Montserrat; García-Gómez, Juan Miguel

    2014-01-01

    The latest advances in eHealth and mHealth have propitiated the rapidly creation and expansion of mobile applications for health care. One of these types of applications are the clinical decision support systems, which nowadays are being implemented in mobile apps to facilitate the access to health care professionals in their daily clinical decisions. The aim of this paper is twofold. Firstly, to make a review of the current systems available in the literature and in commercial stores. Secondly, to analyze a sample of applications in order to obtain some conclusions and recommendations. Two reviews have been done: a literature review on Scopus, IEEE Xplore, Web of Knowledge and PubMed and a commercial review on Google play and the App Store. Five applications from each review have been selected to develop an in-depth analysis and to obtain more information about the mobile clinical decision support systems. Ninety-two relevant papers and 192 commercial apps were found. Forty-four papers were focused only on mobile clinical decision support systems. One hundred seventy-one apps were available on Google play and 21 on the App Store. The apps are designed for general medicine and 37 different specialties, with some features common in all of them despite of the different medical fields objective. The number of mobile clinical decision support applications and their inclusion in clinical practices has risen in the last years. However, developers must be careful with their interface or the easiness of use, which can impoverish the experience of the users.

  12. The role of emotion in clinical decision making: an integrative literature review.

    Science.gov (United States)

    Kozlowski, Desirée; Hutchinson, Marie; Hurley, John; Rowley, Joanne; Sutherland, Joanna

    2017-12-15

    Traditionally, clinical decision making has been perceived as a purely rational and cognitive process. Recently, a number of authors have linked emotional intelligence (EI) to clinical decision making (CDM) and calls have been made for an increased focus on EI skills for clinicians. The objective of this integrative literature review was to identify and synthesise the empirical evidence for a role of emotion in CDM. A systematic search of the bibliographic databases PubMed, PsychINFO, and CINAHL (EBSCO) was conducted to identify empirical studies of clinician populations. Search terms were focused to identify studies reporting clinician emotion OR clinician emotional intelligence OR emotional competence AND clinical decision making OR clinical reasoning. Twenty three papers were retained for synthesis. These represented empirical work from qualitative, quantitative, and mixed-methods approaches and comprised work with a focus on experienced emotion and on skills associated with emotional intelligence. The studies examined nurses (10), physicians (7), occupational therapists (1), physiotherapists (1), mixed clinician samples (3), and unspecified infectious disease experts (1). We identified two main themes in the context of clinical decision making: the subjective experience of emotion; and, the application of emotion and cognition in CDM. Sub-themes under the subjective experience of emotion were: emotional response to contextual pressures; emotional responses to others; and, intentional exclusion of emotion from CDM. Under the application of emotion and cognition in CDM, sub-themes were: compassionate emotional labour - responsiveness to patient emotion within CDM; interdisciplinary tension regarding the significance and meaning of emotion in CDM; and, emotion and moral judgement. Clinicians' experienced emotions can and do affect clinical decision making, although acknowledgement of that is far from universal. Importantly, this occurs in the in the absence of a

  13. Automated electrocardiogram interpretation programs versus cardiologists' triage decision making based on teletransmitted data in patients with suspected acute coronary syndrome

    DEFF Research Database (Denmark)

    Clark, Elaine N; Ripa, Maria Sejersten; Clemmensen, Peter

    2010-01-01

    The aims of this study were to assess the effectiveness of 2 automated electrocardiogram interpretation programs in patients with suspected acute coronary syndrome transported to hospital by ambulance in 1 rural region of Denmark with hospital discharge diagnosis used as the gold standard...

  14. Ictal SPECT Using an Attachable Automated Injector: Clinical Usefulness in the Prediction of Ictal Onset Zone

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung-Ju (Dept. of Neurology, Eulji General Hospital, Eulji Univ. College of Medicine, Seoul (Korea)). e-mail. sangunlee@dreamwiz.com; Lee, Sang Kun (Dept. of Neurology, Seoul National Univ. College of Medicine, Seoul (Korea)); Choi, Jang Wuk (Dept. of Neurology, Seoul National Univ. Hospital, Seoul (Korea)) (and others)

    2009-12-15

    Background: Ictal single-photon emission computed tomography (SPECT) is a valuable method for localizing the ictal onset zone in the presurgical evaluation of patients with intractable epilepsy. Conventional methods used to localize the ictal onset zone have problems with time lag from seizure onset to injection. Purpose: To evaluate the clinical usefulness of a method that we developed, which involves an attachable automated injector (AAI), in reducing time lag and improving the ability to localize the zone of seizure onset. Material and Methods: Patients admitted to the epilepsy monitoring unit (EMU) between January 1, 2003, and June 30, 2008, were included. The definition of ictal onset zone was made by comprehensive review of medical records, magnetic resonance imaging (MRI), data from video electroencephalography (EEG) monitoring, and invasive EEG monitoring if available. We comprehensively evaluated the time lag to injection and the image patterns of ictal SPECT using traditional visual analysis, statistical parametric mapping-assisted, and subtraction ictal SPECT coregistered to an MRI-assisted means of analysis. Image patterns were classified as localizing, lateralizing, and nonlateralizing. The whole number of patients was 99: 48 in the conventional group and 51 in the AAI group. Results: The mean (SD) delay time to injection from seizure onset was 12.4+-12.0 s in the group injected by our AAI method and 40.4+-26.3 s in the group injected by the conventional method (P=0.000). The mean delay time to injection from seizure detection was 3.2+-2.5 s in the group injected by the AAI method and 21.4+-9.7 s in the group injected by the conventional method (P=0.000). The AAI method was superior to the conventional method in localizing the area of seizure onset (36 out of 51 with AAI method vs. 21 out of 48 with conventional method, P=0.009), especially in non-temporal lobe epilepsy (non-TLE) patients (17 out of 27 with AAI method vs. 3 out of 13 with conventional

  15. Ictal SPECT using an attachable automated injector: clinical usefulness in the prediction of ictal onset zone.

    Science.gov (United States)

    Lee, Jung-Ju; Lee, Sang Kun; Choi, Jang Wuk; Kim, Dong-Wook; Park, Kyung Il; Kim, Bom Sahn; Kang, Hyejin; Lee, Dong Soo; Lee, Seo-Young; Kim, Sung Hun; Chung, Chun Kee; Nam, Hyeon Woo; Kim, Kwang Ki

    2009-12-01

    Ictal single-photon emission computed tomography (SPECT) is a valuable method for localizing the ictal onset zone in the presurgical evaluation of patients with intractable epilepsy. Conventional methods used to localize the ictal onset zone have problems with time lag from seizure onset to injection. To evaluate the clinical usefulness of a method that we developed, which involves an attachable automated injector (AAI), in reducing time lag and improving the ability to localize the zone of seizure onset. Patients admitted to the epilepsy monitoring unit (EMU) between January 1, 2003, and June 30, 2008, were included. The definition of ictal onset zone was made by comprehensive review of medical records, magnetic resonance imaging (MRI), data from video electroencephalography (EEG) monitoring, and invasive EEG monitoring if available. We comprehensively evaluated the time lag to injection and the image patterns of ictal SPECT using traditional visual analysis, statistical parametric mapping-assisted, and subtraction ictal SPECT coregistered to an MRI-assisted means of analysis. Image patterns were classified as localizing, lateralizing, and nonlateralizing. The whole number of patients was 99: 48 in the conventional group and 51 in the AAI group. The mean (SD) delay time to injection from seizure onset was 12.4+/-12.0 s in the group injected by our AAI method and 40.4+/-26.3 s in the group injected by the conventional method (P=0.000). The mean delay time to injection from seizure detection was 3.2+/-2.5 s in the group injected by the AAI method and 21.4+/-9.7 s in the group injected by the conventional method (P=0.000). The AAI method was superior to the conventional method in localizing the area of seizure onset (36 out of 51 with AAI method vs. 21 out of 48 with conventional method, P=0.009), especially in non-temporal lobe epilepsy (non-TLE) patients (17 out of 27 with AAI method vs. 3 out of 13 with conventional method, P=0.041), and in lateralizing the

  16. Evaluating a Clinical Decision Support Interface for End-of-Life Nurse Care.

    Science.gov (United States)

    Febretti, Alessandro; Stifter, Janet; Keenan, Gail M; Lopez, Karen D; Johnson, Andrew; Wilkie, Diana J

    2014-01-01

    Clinical Decision Support Systems (CDSS) are tools that assist healthcare personnel in the decision-making process for patient care. Although CDSSs have been successfully deployed in the clinical setting to assist physicians, few CDSS have been targeted at professional nurses, the largest group of health providers. We present our experience in designing and testing a CDSS interface embedded within a nurse care planning and documentation tool. We developed four prototypes based on different CDSS feature designs, and tested them in simulated end-of-life patient handoff sessions with a group of 40 nurse clinicians. We show how our prototypes directed nurses towards an optimal care decision that was rarely performed in unassisted practice. We also discuss the effect of CDSS layout and interface navigation in a nurse's acceptance of suggested actions. These findings provide insights into effective nursing CDSS design that are generalizable to care scenarios different than end-of-life.

  17. Clinical use of patient decision-making aids for stone patients.

    Science.gov (United States)

    Lim, Amy H; Streeper, Necole M; Best, Sara L; Penniston, Kristina L; Nakada, Stephen Y

    2017-08-01

    Patient decision-making aids (PDMAs) help patients make informed healthcare decisions and improve patient satisfaction. The utility of PDMAs for patients considering treatments for urolithiasis has not yet been published. We report our experience using PDMAs developed at our institution in the outpatient clinical setting in patients considering a variety of treatment options for stones. Patients with radiographically confirmed urolithiasis were given PDMAs regarding treatment options for their stone(s) based on their clinical profile. We assessed patients' satisfaction, involvedness, and feeling of making a more informed decision with utilization of the PDMAs using a Likert Scale Questionnaire. Information was also collected regarding previous stone passage, history and type of surgical intervention for urolithiasis, and level of education. Patients (n = 43; 18 males, 23 females and two unknown) 53 +/- 14years old were included. Patients reported that they understood the advantages and disadvantages outlined in the PDMAs (97%), that the PDMAs helped them make a more informed decision (83%) and felt more involved in the decision making process (88%). Patients reported that the aids were presented in a balanced manner and used up-to-date scientific information (100%, 84% respectively). Finally, a majority of the patients prefer an expert's opinion when making a treatment decision (98%) with 73% of patients preferring to form their own opinion based on available information. Previous stone surgery was associated with patients feeling more involved with the decision making process (p = 0.0465). PDMAs have a promising role in shared decision-making in the setting of treatment options for nephrolithiasis.

  18. Towards meaningful medication-related clinical decision support: recommendations for an initial implementation.

    Science.gov (United States)

    Phansalkar, S; Wright, A; Kuperman, G J; Vaida, A J; Bobb, A M; Jenders, R A; Payne, T H; Halamka, J; Bloomrosen, M; Bates, D W

    2011-01-01

    Clinical decision support (CDS) can improve safety, quality, and cost-effectiveness of patient care, especially when implemented in computerized provider order entry (CPOE) applications. Medication-related decision support logic forms a large component of the CDS logic in any CPOE system. However, organizations wishing to implement CDS must either purchase the computable clinical content or develop it themselves. Content provided by vendors does not always meet local expectations. Most organizations lack the resources to customize the clinical content and the expertise to implement it effectively. In this paper, we describe the recommendations of a national expert panel on two basic medication-related CDS areas, specifically, drug-drug interaction (DDI) checking and duplicate therapy checking. The goals of this study were to define a starter set of medication-related alerts that healthcare organizations can implement in their clinical information systems. We also draw on the experiences of diverse institutions to highlight the realities of implementing medication decision support. These findings represent the experiences of institutions with a long history in the domain of medication decision support, and the hope is that this guidance may improve the feasibility and efficiency CDS adoption across healthcare settings.

  19. Doing the right things and doing things right : inpatient drug surveillance assisted by clinical decision support

    NARCIS (Netherlands)

    Helmons, Pieter J.; Suijkerbuijk, Bas O.; Nannan Panday, Prashant V.; Kosterink, Jos G. W.

    Increased budget constraints and a continuous focus on improved quality require an efficient inpatient drug surveillance process. We describe a hospital-wide drug surveillance strategy consisting of a multidisciplinary evaluation of drug surveillance activities and using clinical decision support to

  20. A decision support system for medical mobile devices based on clinical guidelines for tuberculosis

    NARCIS (Netherlands)

    Cazella, Silvio César; Feyh, Rafael; Ben, Angela Jornada

    2014-01-01

    The decision making process conducted by health professionals is strongly linked to the consultations of clinical guidelines, generally available in large text files, making the access to the information very laborious and time consuming. The health area is very fertile for the emergence of

  1. Knowledge of risk factors and the periodontal disease-systemic link in dental students' clinical decisions.

    Science.gov (United States)

    Friesen, Lynn Roosa; Walker, Mary P; Kisling, Rebecca E; Liu, Ying; Williams, Karen B

    2014-09-01

    This study evaluated second-, third-, and fourth-year dental students' ability to identify systemic conditions associated with periodontal disease, risk factors most important for referral, and medications with an effect on the periodontium and their ability to apply this knowledge to make clinical decisions regarding treatment and referral of periodontal patients. A twenty-one question survey was administered at one U.S. dental school in the spring semester of 2012 to elicit the students' knowledge and confidence regarding clinical reasoning. The response rate was 86 percent. Periodontal risk factors were accurately selected by at least 50 percent of students in all three classes; these were poorly controlled diabetes, ≥6 mm pockets posteriorly, and lack of response to previous non-surgical therapy. Confidence in knowledge, knowledge of risk factors, and knowledge of medications with an effect on the periodontium improved with training and were predictive of better referral decision making. The greatest impact of training was seen on the students' ability to make correct decisions about referral and treatment for seven clinical scenarios. Although the study found a large increase in the students' abilities from the second through fourth years, the mean of 4.6 (out of 7) for the fourth-year students shows that, on average, those students missed correct treatment or referral on more than two of seven clinical cases. These results suggest that dental curricula should emphasize more critical decision making with respect to referral and treatment criteria in managing the periodontal patient.

  2. Competencies in nursing students for organized forms of clinical moral deliberation and decision-making

    NARCIS (Netherlands)

    dr. Bart Cusveller; Jeanette den Uil-Westerlaken

    2014-01-01

    Bachelor-prepared nurses are expected to be competent in moral deliberation and decision-making (MDD) in clinical practice. It is unclear, however, how this competence develops in nursing students. This study explores the development of nursing students’ competence for participating in organized

  3. The interaction of patient race, provider bias, and clinical ambiguity on pain management decisions.

    Science.gov (United States)

    Hirsh, Adam T; Hollingshead, Nicole A; Ashburn-Nardo, Leslie; Kroenke, Kurt

    2015-06-01

    Although racial disparities in pain care are widely reported, much remains to be known about the role of provider and contextual factors. We used computer-simulated patients to examine the influence of patient race, provider racial bias, and clinical ambiguity on pain decisions. One hundred twenty-nine medical residents/fellows made assessment (pain intensity) and treatment (opioid and nonopioid analgesics) decisions for 12 virtual patients with acute pain. Race (black/white) and clinical ambiguity (high/low) were manipulated across vignettes. Participants completed the Implicit Association Test and feeling thermometers, which assess implicit and explicit racial biases, respectively. Individual- and group-level analyses indicated that race and ambiguity had an interactive effect on providers' decisions, such that decisions varied as a function of ambiguity for white but not for black patients. Individual differences across providers were observed for the effect of race and ambiguity on decisions; however, providers' implicit and explicit biases did not account for this variability. These data highlight the complexity of racial disparities and suggest that differences in care between white and black patients are, in part, attributable to the nature (ie, ambiguity) of the clinical scenario. The current study suggests that interventions to reduce disparities should differentially target patient, provider, and contextual factors. This study examined the unique and collective influence of patient race, provider racial bias, and clinical ambiguity on providers' pain management decisions. These results could inform the development of interventions aimed at reducing disparities and improving pain care. Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.

  4. Performance of Kiestra total laboratory automation combined with MS in clinical microbiology practice

    NARCIS (Netherlands)

    Mutters, Nico T.; Hodiamont, Caspar J.; de Jong, Menno D.; Overmeijer, Hendri P. J.; van den Boogaard, Mandy; Visser, Caroline E.

    2014-01-01

    Microbiological laboratories seek technologically innovative solutions to cope with large numbers of samples and limited personnel and financial resources. One platform that has recently become available is the Kiestra Total Laboratory Automation (TLA) system (BD Kiestra B.V., the Netherlands). This

  5. [A computerised clinical decision-support system for the management of depression in Primary Care].

    Science.gov (United States)

    Aragonès, Enric; Comín, Eva; Cavero, Myriam; Pérez, Víctor; Molina, Cristina; Palao, Diego

    Despite its clinical relevance and its importance as a public health problem, there are major gaps in the management of depression. Evidence-based clinical guidelines are useful to improve processes and clinical outcomes. In order to make their implementation easier these guidelines have been transformed into computerised clinical decision support systems. In this article, a description is presented on the basics and characteristics of a new computerised clinical guideline for the management of major depression, developed in the public health system in Catalonia. This tool helps the clinician to establish reliable and accurate diagnoses of depression, to choose the best treatment a priori according to the disease and the patient characteristics. It also emphasises the importance of systematic monitoring to assess the clinical course, and to adjust therapeutic interventions to the patient's needs at all times. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

  6. Enhancing nurse and physician collaboration in clinical decision making through high-fidelity interdisciplinary simulation training.

    Science.gov (United States)

    Maxson, Pamela M; Dozois, Eric J; Holubar, Stefan D; Wrobleski, Diane M; Dube, Joyce A Overman; Klipfel, Janee M; Arnold, Jacqueline J

    2011-01-01

    To determine whether interdisciplinary simulation team training can positively affect registered nurse and/or physician perceptions of collaboration in clinical decision making. Between March 1 and April 21, 2009, a convenience sample of volunteer nurses and physicians was recruited to undergo simulation training consisting of a team response to 3 clinical scenarios. Participants completed the Collaboration and Satisfaction About Care Decisions (CSACD) survey before training and at 2 weeks and 2 months after training. Differences in CSACD summary scores between the time points were assessed with paired t tests. Twenty-eight health care professionals (19 nurses, 9 physicians) underwent simulation training. Nurses were of similar age to physicians (27.3 vs 34.5 years; p = .82), were more likely to be women (95.0% vs 12.5%; p nurses and physicians (p = .04) and that both medical and nursing concerns influence the decision-making process (p = .02). Pretest CSACD analysis revealed that most participants were dissatisfied with the decision-making process. The CSACD summary score showed significant improvement from baseline to 2 weeks (4.2 to 5.1; p nurses and physicians and enhanced the patient care decision-making process.

  7. Uninformed Clinical Decisions Resulting From Lack of Adherence Assessment in Children with New Onset Epilepsy

    Science.gov (United States)

    Modi, Avani C.; Wu, Yelena P.; Guilfoyle, Shanna M.; Glauser, Tracy A.

    2012-01-01

    This study examined the relationship between non-adherence to antiepileptic drug (AED) therapy and clinical decision-making in a cohort of 112 children with newly-diagnosed epilepsy. AED adherence was monitored using electronic monitoring over the first six months of therapy. The primary outcome measure was rate of uninformed clinical decisions as defined by number of participants with AED dosage or drug changes to address continued seizures who demonstrated non-adherence prior to the seizure. Among the 52 (47%) participants who had an AED change for continued seizures, 30 (27% of the overall cohort) had imperfect medication adherence prior to their seizures. A quarter of children with new onset epilepsy had uninformed medication changes because adherence was not rigorously assessed in clinical practice. Results highlight the importance of routinely assessing medication adherence in this population. PMID:23159375

  8. Workshop on using natural language processing applications for enhancing clinical decision making: an executive summary.

    Science.gov (United States)

    Pai, Vinay M; Rodgers, Mary; Conroy, Richard; Luo, James; Zhou, Ruixia; Seto, Belinda

    2014-02-01

    In April 2012, the National Institutes of Health organized a two-day workshop entitled 'Natural Language Processing: State of the Art, Future Directions and Applications for Enhancing Clinical Decision-Making' (NLP-CDS). This report is a summary of the discussions during the second day of the workshop. Collectively, the workshop presenters and participants emphasized the need for unstructured clinical notes to be included in the decision making workflow and the need for individualized longitudinal data tracking. The workshop also discussed the need to: (1) combine evidence-based literature and patient records with machine-learning and prediction models; (2) provide trusted and reproducible clinical advice; (3) prioritize evidence and test results; and (4) engage healthcare professionals, caregivers, and patients. The overall consensus of the NLP-CDS workshop was that there are promising opportunities for NLP and CDS to deliver cognitive support for healthcare professionals, caregivers, and patients.

  9. Assessing an Adolescent's Capacity for Autonomous Decision-Making in Clinical Care.

    Science.gov (United States)

    Michaud, Pierre-André; Blum, Robert Wm; Benaroyo, Lazare; Zermatten, Jean; Baltag, Valentina

    2015-10-01

    The purpose of this article is to provide policy guidance on how to assess the capacity of minor adolescents for autonomous decision-making without a third party authorization, in the field of clinical care. In June 2014, a two-day meeting gathered 20 professionals from all continents, working in the field of adolescent medicine, neurosciences, developmental and clinical psychology, sociology, ethics, and law. Formal presentations and discussions were based on a literature search and the participants' experience. The assessment of adolescent decision-making capacity includes the following: (1) a review of the legal context consistent with the principles of the Convention on the Rights of the Child; (2) an empathetic relationship between the adolescent and the health care professional/team; (3) the respect of the adolescent's developmental stage and capacities; (4) the inclusion, if relevant, of relatives, peers, teachers, or social and mental health providers with the adolescent's consent; (5) the control of coercion and other social forces that influence decision-making; and (6) a deliberative stepwise appraisal of the adolescent's decision-making process. This stepwise approach, already used among adults with psychiatric disorders, includes understanding the different facets of the given situation, reasoning on the involved issues, appreciating the outcomes linked with the decision(s), and expressing a choice. Contextual and psychosocial factors play pivotal roles in the assessment of adolescents' decision-making capacity. The evaluation must be guided by a well-established procedure, and health professionals should be trained accordingly. These proposals are the first to have been developed by a multicultural, multidisciplinary expert panel. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  10. Reward-related decision making in older adults: relationship to clinical presentation of depression.

    Science.gov (United States)

    McGovern, Amanda R; Alexopoulos, George S; Yuen, Genevieve S; Morimoto, Sarah Shizuko; Gunning-Dixon, Faith M

    2014-11-01

    Impairment in reward processes has been found in individuals with depression and in the aging population. The purpose of this study was twofold: (1) to use an affective neuroscience probe to identify abnormalities in reward-related decision making in late-life depression; and (2) to examine the relationship of reward-related decision making abnormalities in depressed, older adults to the clinical expression of apathy in depression. We hypothesized that relative to older, healthy subjects, depressed, older patients would exhibit impaired decision making and that apathetic, depressed patients would show greater impairment in decision making than non-apathetic, depressed patients. We used the Iowa Gambling Task to examine reward-related decision making in 60 non-demented, older patients with non-psychotic major depression and 36 older, psychiatrically healthy participants. Apathy was quantified using the Apathy Evaluation Scale. Of those with major depression, 18 individuals reported clinically significant apathy, whereas 42 participants did not have apathy. Older adults with depression and healthy comparison participants did not differ in their performance on the Iowa Gambling Task. However, apathetic, depressed older adults adopted an advantageous strategy and selected cards from the conservative decks compared with non-apathetic, depressed older adults. Non-apathetic, depressed patients showed a failure to adopt a conservative strategy and persisted in making risky decisions throughout the task. This study indicates that apathy in older, depressed adults is associated with a conservative response style on a behavioral probe of the systems involved in reward-related decision making. This conservative response style may be the result of reduced sensitivity to rewards in apathetic individuals. Copyright © 2014 John Wiley & Sons, Ltd.

  11. Automated Cell Enrichment of Cytomegalovirus-specific T cells for Clinical Applications using the Cytokine-capture System.

    Science.gov (United States)

    Kumaresan, Pappanaicken; Figliola, Mathew; Moyes, Judy S; Huls, M Helen; Tewari, Priti; Shpall, Elizabeth J; Champlin, Richard; Cooper, Laurence J N

    2015-10-05

    The adoptive transfer of pathogen-specific T cells can be used to prevent and treat opportunistic infections such as cytomegalovirus (CMV) infection occurring after allogeneic hematopoietic stem-cell transplantation. Viral-specific T cells from allogeneic donors, including third party donors, can be propagated ex vivo in compliance with current good manufacturing practice (cGMP), employing repeated rounds of antigen-driven stimulation to selectively propagate desired T cells. The identification and isolation of antigen-specific T cells can also be undertaken based upon the cytokine capture system of T cells that have been activated to secrete gamma-interferon (IFN-γ). However, widespread human application of the cytokine capture system (CCS) to help restore immunity has been limited as the production process is time-consuming and requires a skilled operator. The development of a second-generation cell enrichment device such as CliniMACS Prodigy now enables investigators to generate viral-specific T cells using an automated, less labor-intensive system. This device separates magnetically labeled cells from unlabeled cells using magnetic activated cell sorting technology to generate clinical-grade products, is engineered as a closed system and can be accessed and operated on the benchtop. We demonstrate the operation of this new automated cell enrichment device to manufacture CMV pp65-specific T cells obtained from a steady-state apheresis product obtained from a CMV seropositive donor. These isolated T cells can then be directly infused into a patient under institutional and federal regulatory supervision. All the bio-processing steps including removal of red blood cells, stimulation of T cells, separation of antigen-specific T cells, purification, and washing are fully automated. Devices such as this raise the possibility that T cells for human application can be manufactured outside of dedicated good manufacturing practice (GMP) facilities and instead be produced

  12. Automated Detection of Malarial Retinopathy in Digital Fundus Images for Improved Diagnosis in Malawian Children with Clinically Defined Cerebral Malaria

    Science.gov (United States)

    Joshi, Vinayak; Agurto, Carla; Barriga, Simon; Nemeth, Sheila; Soliz, Peter; MacCormick, Ian J.; Lewallen, Susan; Taylor, Terrie E.; Harding, Simon P.

    2017-02-01

    Cerebral malaria (CM), a complication of malaria infection, is the cause of the majority of malaria-associated deaths in African children. The standard clinical case definition for CM misclassifies ~25% of patients, but when malarial retinopathy (MR) is added to the clinical case definition, the specificity improves from 61% to 95%. Ocular fundoscopy requires expensive equipment and technical expertise not often available in malaria endemic settings, so we developed an automated software system to analyze retinal color images for MR lesions: retinal whitening, vessel discoloration, and white-centered hemorrhages. The individual lesion detection algorithms were combined using a partial least square classifier to determine the presence or absence of MR. We used a retrospective retinal image dataset of 86 pediatric patients with clinically defined CM (70 with MR and 16 without) to evaluate the algorithm performance. Our goal was to reduce the false positive rate of CM diagnosis, and so the algorithms were tuned at high specificity. This yielded sensitivity/specificity of 95%/100% for the detection of MR overall, and 65%/94% for retinal whitening, 62%/100% for vessel discoloration, and 73%/96% for hemorrhages. This automated system for detecting MR using retinal color images has the potential to improve the accuracy of CM diagnosis.

  13. Physicians' perspectives on communication and decision making in clinical encounters for treatment of latent tuberculosis infection.

    Science.gov (United States)

    Dobler, Claudia C; Bosnic-Anticevich, Sinthia; Armour, Carol L

    2018-01-01

    The aim of the study was to explore the views of tuberculosis (TB) physicians on treatment of latent TB infection (LTBI), focusing on decision making and communication in clinical practice. 20 Australian TB physicians participated in a semistructured interview in person or over the telephone. Interviews were recorded, transcribed and analysed thematically. The study identified challenges that physicians face when discussing treatment for LTBI with patients. These included difficulties explaining the concept of latency (in particular to patients from culturally and linguistically diverse backgrounds) and providing guidance to patients while still framing treatment decisions as a choice. Tailored estimates of the risk of developing TB and the risk of developing an adverse effect from LTBI treatment were considered the most important information for decision making and discussion with patients. Physicians acknowledged that there is a significant amount of unwarranted treatment variation, which they attributed to the lack of evidence about the risk-benefit balance of LTBI treatment in certain scenarios and guidelines that refer to the need for case-by-case decision making in many instances. In order to successfully implement LTBI treatment at a clinical level, consideration should be given to research on how to best address communication challenges arising in clinical encounters.

  14. Physicians' perspectives on communication and decision making in clinical encounters for treatment of latent tuberculosis infection

    Directory of Open Access Journals (Sweden)

    Claudia C. Dobler

    2018-03-01

    Full Text Available The aim of the study was to explore the views of tuberculosis (TB physicians on treatment of latent TB infection (LTBI, focusing on decision making and communication in clinical practice. 20 Australian TB physicians participated in a semistructured interview in person or over the telephone. Interviews were recorded, transcribed and analysed thematically. The study identified challenges that physicians face when discussing treatment for LTBI with patients. These included difficulties explaining the concept of latency (in particular to patients from culturally and linguistically diverse backgrounds and providing guidance to patients while still framing treatment decisions as a choice. Tailored estimates of the risk of developing TB and the risk of developing an adverse effect from LTBI treatment were considered the most important information for decision making and discussion with patients. Physicians acknowledged that there is a significant amount of unwarranted treatment variation, which they attributed to the lack of evidence about the risk–benefit balance of LTBI treatment in certain scenarios and guidelines that refer to the need for case-by-case decision making in many instances. In order to successfully implement LTBI treatment at a clinical level, consideration should be given to research on how to best address communication challenges arising in clinical encounters.

  15. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems.

    Science.gov (United States)

    DesAutels, Spencer J; Fox, Zachary E; Giuse, Dario A; Williams, Annette M; Kou, Qing-Hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

    2016-01-01

    Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems.

  16. Using Best Practices to Extract, Organize, and Reuse Embedded Decision Support Content Knowledge Rules from Mature Clinical Systems

    Science.gov (United States)

    DesAutels, Spencer J.; Fox, Zachary E.; Giuse, Dario A.; Williams, Annette M.; Kou, Qing-hua; Weitkamp, Asli; Neal R, Patel; Bettinsoli Giuse, Nunzia

    2016-01-01

    Clinical decision support (CDS) knowledge, embedded over time in mature medical systems, presents an interesting and complex opportunity for information organization, maintenance, and reuse. To have a holistic view of all decision support requires an in-depth understanding of each clinical system as well as expert knowledge of the latest evidence. This approach to clinical decision support presents an opportunity to unify and externalize the knowledge within rules-based decision support. Driven by an institutional need to prioritize decision support content for migration to new clinical systems, the Center for Knowledge Management and Health Information Technology teams applied their unique expertise to extract content from individual systems, organize it through a single extensible schema, and present it for discovery and reuse through a newly created Clinical Support Knowledge Acquisition and Archival Tool (CS-KAAT). CS-KAAT can build and maintain the underlying knowledge infrastructure needed by clinical systems. PMID:28269846

  17. The use of emotional intelligence capabilities in clinical reasoning and decision-making: A qualitative, exploratory study.

    Science.gov (United States)

    Hutchinson, Marie; Hurley, John; Kozlowski, Desirée; Whitehair, Leeann

    2018-02-01

    To explore clinical nurses' experiences of using emotional intelligence capabilities during clinical reasoning and decision-making. There has been little research exploring whether, or how, nurses employ emotional intelligence (EI) in clinical reasoning and decision-making. Qualitative phase of a larger mixed-methods study. Semistructured qualitative interviews with a purposive sample of registered nurses (n = 12) following EI training and coaching. Constructivist thematic analysis was employed to analyse the narrative transcripts. Three themes emerged: the sensibility to engage EI capabilities in clinical contexts, motivation to actively engage with emotions in clinical decision-making and incorporating emotional and technical perspectives in decision-making. Continuing to separate cognition and emotion in research, theorising and scholarship on clinical reasoning is counterproductive. Understanding more about nurses' use of EI has the potential to improve the calibre of decisions, and the safety and quality of care delivered. © 2017 John Wiley & Sons Ltd.

  18. Automated population of an i2b2 clinical data warehouse from an openEHR-based data repository.

    Science.gov (United States)

    Haarbrandt, Birger; Tute, Erik; Marschollek, Michael

    2016-10-01

    Detailed Clinical Model (DCM) approaches have recently seen wider adoption. More specifically, openEHR-based application systems are now used in production in several countries, serving diverse fields of application such as health information exchange, clinical registries and electronic medical record systems. However, approaches to efficiently provide openEHR data to researchers for secondary use have not yet been investigated or established. We developed an approach to automatically load openEHR data instances into the open source clinical data warehouse i2b2. We evaluated query capabilities and the performance of this approach in the context of the Hanover Medical School Translational Research Framework (HaMSTR), an openEHR-based data repository. Automated creation of i2b2 ontologies from archetypes and templates and the integration of openEHR data instances from 903 patients of a paediatric intensive care unit has been achieved. In total, it took an average of ∼2527s to create 2.311.624 facts from 141.917 XML documents. Using the imported data, we conducted sample queries to compare the performance with two openEHR systems and to investigate if this representation of data is feasible to support cohort identification and record level data extraction. We found the automated population of an i2b2 clinical data warehouse to be a feasible approach to make openEHR data instances available for secondary use. Such an approach can facilitate timely provision of clinical data to researchers. It complements analytics based on the Archetype Query Language by allowing querying on both, legacy clinical data sources and openEHR data instances at the same time and by providing an easy-to-use query interface. However, due to different levels of expressiveness in the data models, not all semantics could be preserved during the ETL process. Copyright © 2016 Elsevier Inc. All rights reserved.

  19. Identifying design considerations for a shared decision aid for use at the point of outpatient clinical care: An ethnographic study at an inner city clinic.

    Science.gov (United States)

    Hajizadeh, Negin; Perez Figueroa, Rafael E; Uhler, Lauren M; Chiou, Erin; Perchonok, Jennifer E; Montague, Enid

    2013-03-06

    Computerized decision aids could facilitate shared decision-making at the point of outpatient clinical care. The objective of this study was to investigate whether a computerized shared decision aid would be feasible to implement in an inner-city clinic by evaluating the current practices in shared decision-making, clinicians' use of computers, patient and clinicians' attitudes and beliefs toward computerized decision aids, and the influence of time on shared decision-making. Qualitative data analysis of observations and semi-structured interviews with patients and clinicians at an inner-city outpatient clinic. The findings provided an exploratory look at the prevalence of shared decision-making and attitudes about health information technology and decision aids. A prominent barrier to clinicians engaging in shared decision-making was a lack of perceived patient understanding of medical information. Some patients preferred their clinicians make recommendations for them rather than engage in formal shared decision-making. Health information technology was an integral part of the clinic visit and welcomed by most clinicians and patients. Some patients expressed the desire to engage with health information technology such as viewing their medical information on the computer screen with their clinicians. All participants were receptive to the idea of a decision aid integrated within the clinic visit although some clinicians were concerned about the accuracy of prognostic estimates for complex medical problems. We identified several important considerations for the design and implementation of a computerized decision aid including opportunities to: bridge clinician-patient communication about medical information while taking into account individual patients' decision-making preferences, complement expert clinician judgment with prognostic estimates, take advantage of patient waiting times, and make tasks involved during the clinic visit more efficient. These findings

  20. Improving Decision Making about Genetic Testing in the Clinic: An Overview of Effective Knowledge Translation Interventions.

    Science.gov (United States)

    Légaré, France; Robitaille, Hubert; Gane, Claire; Hébert, Jessica; Labrecque, Michel; Rousseau, François

    2016-01-01

    Knowledge translation (KT) interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties. We sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing. We searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153) published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC) and Consumers and Communication. We retrieved 2473 unique trials of which we retained only 28 (1%). Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1) and educational outreach (n = 1). Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15), communication of DNA-based disease risk estimates (n = 7), personalized risk communication (n = 3) and mobile phone messaging (n = 1). Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective. More research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations.

  1. Development of a clinical decision support system for diabetes care: A pilot study.

    Directory of Open Access Journals (Sweden)

    Livvi Li Wei Sim

    Full Text Available Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require

  2. Improving Decision Making about Genetic Testing in the Clinic: An Overview of Effective Knowledge Translation Interventions.

    Directory of Open Access Journals (Sweden)

    France Légaré

    Full Text Available Knowledge translation (KT interventions are attempts to change behavior in keeping with scientific evidence. While genetic tests are increasingly available to healthcare consumers in the clinic, evidence about their benefits is unclear and decisions about genetic testing are thus difficult for all parties.We sought to identify KT interventions that involved decisions about genetic testing in the clinical context and to assess their effectiveness for improving decision making in terms of behavior change, increased knowledge and wellbeing.We searched for trials assessing KT interventions in the context of genetic testing up to March 2014 in all systematic reviews (n = 153 published by two Cochrane review groups: Effective Practice and Organisation of Care (EPOC and Consumers and Communication.We retrieved 2473 unique trials of which we retained only 28 (1%. Two EPOC reviews yielded two trials of KT interventions: audit and feedback (n = 1 and educational outreach (n = 1. Both targeted health professionals and the KT intervention they assessed was found to be effective. Four Consumers and Communication reviews yielded 26 trials: decision aids (n = 15, communication of DNA-based disease risk estimates (n = 7, personalized risk communication (n = 3 and mobile phone messaging (n = 1. Among these, 25 trials targeted only health consumers or patients and the KT interventions were found to be effective in four trials, partly effective in seven, and ineffective in four. Lastly, only one trial targeted both physicians and patients and was found to be effective.More research on the effectiveness of KT interventions regarding genetic testing in the clinical context may contribute to patients making informed value-based decisions and drawing the maximum benefit from clinical applications of genetic and genomic innovations.

  3. An RDF/OWL knowledge base for query answering and decision support in clinical pharmacogenetics.

    Science.gov (United States)

    Samwald, Matthias; Freimuth, Robert; Luciano, Joanne S; Lin, Simon; Powers, Robert L; Marshall, M Scott; Adlassnig, Klaus-Peter; Dumontier, Michel; Boyce, Richard D

    2013-01-01

    Genetic testing for personalizing pharmacotherapy is bound to become an important part of clinical routine. To address associated issues with data management and quality, we are creating a semantic knowledge base for clinical pharmacogenetics. The knowledge base is made up of three components: an expressive ontology formalized in the Web Ontology Language (OWL 2 DL), a Resource Description Framework (RDF) model for capturing detailed results of manual annotation of pharmacogenomic information in drug product labels, and an RDF conversion of relevant biomedical datasets. Our work goes beyond the state of the art in that it makes both automated reasoning as well as query answering as simple as possible, and the reasoning capabilities go beyond the capabilities of previously described ontologies.

  4. Considerations for automated machine learning in clinical metabolic profiling: Altered homocysteine plasma concentration associated with metformin exposure.

    Science.gov (United States)

    Orlenko, Alena; Moore, Jason H; Orzechowski, Patryk; Olson, Randal S; Cairns, Junmei; Caraballo, Pedro J; Weinshilboum, Richard M; Wang, Liewei; Breitenstein, Matthew K

    2018-01-01

    With the maturation of metabolomics science and proliferation of biobanks, clinical metabolic profiling is an increasingly opportunistic frontier for advancing translational clinical research. Automated Machine Learning (AutoML) approaches provide exciting opportunity to guide feature selection in agnostic metabolic profiling endeavors, where potentially thousands of independent data points must be evaluated. In previous research, AutoML using high-dimensional data of varying types has been demonstrably robust, outperforming traditional approaches. However, considerations for application in clinical metabolic profiling remain to be evaluated. Particularly, regarding the robustness of AutoML to identify and adjust for common clinical confounders. In this study, we present a focused case study regarding AutoML considerations for using the Tree-Based Optimization Tool (TPOT) in metabolic profiling of exposure to metformin in a biobank cohort. First, we propose a tandem rank-accuracy measure to guide agnostic feature selection and corresponding threshold determination in clinical metabolic profiling endeavors. Second, while AutoML, using default parameters, demonstrated potential to lack sensitivity to low-effect confounding clinical covariates, we demonstrated residual training and adjustment of metabolite features as an easily applicable approach to ensure AutoML adjustment for potential confounding characteristics. Finally, we present increased homocysteine with long-term exposure to metformin as a potentially novel, non-replicated metabolite association suggested by TPOT; an association not identified in parallel clinical metabolic profiling endeavors. While warranting independent replication, our tandem rank-accuracy measure suggests homocysteine to be the metabolite feature with largest effect, and corresponding priority for further translational clinical research. Residual training and adjustment for a potential confounding effect by BMI only slightly modified

  5. Microbleed detection using automated segmentation (MIDAS): a new method applicable to standard clinical MR images.

    Science.gov (United States)

    Seghier, Mohamed L; Kolanko, Magdalena A; Leff, Alexander P; Jäger, Hans R; Gregoire, Simone M; Werring, David J

    2011-03-23

    Cerebral microbleeds, visible on gradient-recalled echo (GRE) T2* MRI, have generated increasing interest as an imaging marker of small vessel diseases, with relevance for intracerebral bleeding risk or brain dysfunction. Manual rating methods have limited reliability and are time-consuming. We developed a new method for microbleed detection using automated segmentation (MIDAS) and compared it with a validated visual rating system. In thirty consecutive stroke service patients, standard GRE T2* images were acquired and manually rated for microbleeds by a trained observer. After spatially normalizing each patient's GRE T2* images into a standard stereotaxic space, the automated microbleed detection algorithm (MIDAS) identified cerebral microbleeds by explicitly incorporating an "extra" tissue class for abnormal voxels within a unified segmentation-normalization model. The agreement between manual and automated methods was assessed using the intraclass correlation coefficient (ICC) and Kappa statistic. We found that MIDAS had generally moderate to good agreement with the manual reference method for the presence of lobar microbleeds (Kappa = 0.43, improved to 0.65 after manual exclusion of obvious artefacts). Agreement for the number of microbleeds was very good for lobar regions: (ICC = 0.71, improved to ICC = 0.87). MIDAS successfully detected all patients with multiple (≥2) lobar microbleeds. MIDAS can identify microbleeds on standard MR datasets, and with an additional rapid editing step shows good agreement with a validated visual rating system. MIDAS may be useful in screening for multiple lobar microbleeds.

  6. Clinical intuition in the nursing process and decision-making-A mixed-studies review.

    Science.gov (United States)

    Melin-Johansson, Christina; Palmqvist, Rebecca; Rönnberg, Linda

    2017-12-01

    To review what is characteristic of registered nurses' intuition in clinical settings, in relationships and in the nursing process. Intuition is a controversial concept and nurses believe that there are difficulties in how they should explain their nursing actions or decisions based on intuition. Much of the evidence from the body of research indicates that nurses value their intuition in a variety of clinical settings. More information on how nurses integrate intuition as a core element in daily clinical work would contribute to an improved understanding on how they go about this. Intuition deserves a place in evidence-based activities, where intuition is an important component associated with the nursing process. An integrative review strengthened with a mixed-studies review. Literature searches were conducted in the databases CINAHL, PubMed and PsycINFO, and literature published 1985-2016 were included. The findings in the studies were analysed with content analysis, and the synthesis process entailed a reasoning between the authors. After a quality assessment, 16 studies were included. The analysis and synthesis resulted in three categories. The characteristics of intuition in the nurse's daily clinical activities include application, assertiveness and experiences; in the relationships with patients' intuition include unique connections, mental and bodily responses, and personal qualities; and in the nursing process include support and guidance, component and clues in decision-making, and validating decisions. Intuition is more than simply a "gut feeling," and it is a process based on knowledge and care experience and has a place beside research-based evidence. Nurses integrate both analysis and synthesis of intuition alongside objective data when making decisions. They should rely on their intuition and use this knowledge in clinical practice as a support in decision-making, which increases the quality and safety of patient care. We find that intuition plays a

  7. Clinical decision support systems in child and adolescent psychiatry: a systematic review.

    Science.gov (United States)

    Koposov, Roman; Fossum, Sturla; Frodl, Thomas; Nytrø, Øystein; Leventhal, Bennett; Sourander, Andre; Quaglini, Silvana; Molteni, Massimo; de la Iglesia Vayá, María; Prokosch, Hans-Ulrich; Barbarini, Nicola; Milham, Michael Peter; Castellanos, Francisco Xavier; Skokauskas, Norbert

    2017-11-01

    Psychiatric disorders are amongst the most prevalent and impairing conditions in childhood and adolescence. Unfortunately, it is well known that general practitioners (GPs) and other frontline health providers (i.e., child protection workers, public health nurses, and pediatricians) are not adequately trained to address these ubiquitous problems (Braddick et al. Child and Adolescent mental health in Europe: infrastructures, policy and programmes, European Communities, 2009; Levav et al. Eur Child Adolesc Psychiatry 13:395-401, 2004). Advances in technology may offer a solution to this problem with clinical decision support systems (CDSS) that are designed to help professionals make sound clinical decisions in real time. This paper offers a systematic review of currently available CDSS for child and adolescent mental health disorders prepared according to the PRISMA-Protocols (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols). Applying strict eligibility criteria, the identified studies (n = 5048) were screened. Ten studies, describing eight original clinical decision support systems for child and adolescent psychiatric disorders, fulfilled inclusion criteria. Based on this systematic review, there appears to be a need for a new, readily available CDSS for child neuropsychiatric disorder which promotes evidence-based, best practices, while enabling consideration of national variation in practices by leveraging data-reuse to generate predictions regarding treatment outcome, addressing a broader cluster of clinical disorders, and targeting frontline practice environments.

  8. Clinical decision support for whole genome sequence information leveraging a service-oriented architecture: a prototype.

    Science.gov (United States)

    Welch, Brandon M; Rodriguez-Loya, Salvador; Eilbeck, Karen; Kawamoto, Kensaku

    2014-01-01

    Whole genome sequence (WGS) information could soon be routinely available to clinicians to support the personalized care of their patients. At such time, clinical decision support (CDS) integrated into the clinical workflow will likely be necessary to support genome-guided clinical care. Nevertheless, developing CDS capabilities for WGS information presents many unique challenges that need to be overcome for such approaches to be effective. In this manuscript, we describe the development of a prototype CDS system that is capable of providing genome-guided CDS at the point of care and within the clinical workflow. To demonstrate the functionality of this prototype, we implemented a clinical scenario of a hypothetical patient at high risk for Lynch Syndrome based on his genomic information. We demonstrate that this system can effectively use service-oriented architecture principles and standards-based components to deliver point of care CDS for WGS information in real-time.

  9. Development of Decision-Making Automated System for Optimal Placement of Physical Access Control System’s Elements

    Science.gov (United States)

    Danilova, Olga; Semenova, Zinaida

    2018-04-01

    The objective of this study is a detailed analysis of physical protection systems development for information resources. The optimization theory and decision-making mathematical apparatus is used to formulate correctly and create an algorithm of selection procedure for security systems optimal configuration considering the location of the secured object’s access point and zones. The result of this study is a software implementation scheme of decision-making system for optimal placement of the physical access control system’s elements.

  10. Clinical Decision Making in the Management of Patients With Cervicogenic Dizziness: A Case Series.

    Science.gov (United States)

    Jung, Francis C; Mathew, Sherin; Littmann, Andrew E; MacDonald, Cameron W

    2017-11-01

    Study Design Case series. Background Although growing recognition of cervicogenic dizziness (CGD) is emerging, there is still no gold standard for the diagnosis of CGD. The purpose of this case series is to describe the clinical decision making utilized in the management of 7 patients presenting with CGD. Case Description Patients presenting with neck pain and accompanying subjective symptoms, including dizziness, unsteadiness, light-headedness, and visual disturbance, were selected. Clinical evidence of a temporal relationship between neck pain and dizziness, with or without sensorimotor disturbances, was assessed. Clinical decision making followed a 4-step process, informed by the current available best evidence. Outcome measures included the numeric rating scale for dizziness and neck pain, the Dizziness Handicap Inventory, Patient-Specific Functional Scale, and global rating of change. Outcomes Seven patients (mean age, 57 years; range, 31-86 years; 7 female) completed physical therapy management at an average of 13 sessions (range, 8-30 sessions) over a mean of 7 weeks. Clinically meaningful improvements were observed in the numeric rating scale for dizziness (mean difference, 5.7; 95% confidence interval [CI]: 4.0, 7.5), neck pain (mean difference, 5.4; 95% CI: 3.8, 7.1), and the Dizziness Handicap Inventory (mean difference, 32.6; 95% CI: 12.9, 52.2) at discontinuation. Patients also demonstrated overall satisfaction via the Patient-Specific Functional Scale (mean difference, 9) and global rating of change (mean, +6). Discussion This case series describes the physical therapist decision making, management, and outcomes in patients with CGD. Further investigation is warranted to develop a valid clinical decision-making guideline to inform management of patients with CGD. Level of Evidence Diagnosis, therapy, level 4. J Orthop Sports Phys Ther 2017;47(11):874-884. Epub 9 Oct 2017. doi:10.2519/jospt.2017.7425.

  11. The potential value on medication safety of a clinical decision support system in intensive care patients with renal insufficiency.

    NARCIS (Netherlands)

    Helmons, P.J.; Grouls, R.J.E.; Roos, A.N.; Bindels, A.J.G.H.; Clercq, de P.A.; Wessels-Basten, S.J.W.; Ackerman, E.W.; Korsten, H.H.M.

    2007-01-01

    Clinical decision support systems (CDSS) are defined as electronic or non-electronic systems designed to aid in clinical decision making, using characteristics of individual patients to generate patient-specific assessments or recommendations that are then presented to clinicians for consideration

  12. A knowledge- and model-based system for automated weaning from mechanical ventilation: technical description and first clinical application.

    Science.gov (United States)

    Schädler, Dirk; Mersmann, Stefan; Frerichs, Inéz; Elke, Gunnar; Semmel-Griebeler, Thomas; Noll, Oliver; Pulletz, Sven; Zick, Günther; David, Matthias; Heinrichs, Wolfgang; Scholz, Jens; Weiler, Norbert

    2014-10-01

    To describe the principles and the first clinical application of a novel prototype automated weaning system called Evita Weaning System (EWS). EWS allows an automated control of all ventilator settings in pressure controlled and pressure support mode with the aim of decreasing the respiratory load of mechanical ventilation. Respiratory load takes inspired fraction of oxygen, positive end-expiratory pressure, pressure amplitude and spontaneous breathing activity into account. Spontaneous breathing activity is assessed by the number of controlled breaths needed to maintain a predefined respiratory rate. EWS was implemented as a knowledge- and model-based system that autonomously and remotely controlled a mechanical ventilator (Evita 4, Dräger Medical, Lübeck, Germany). In a selected case study (n = 19 patients), ventilator settings chosen by the responsible physician were compared with the settings 10 min after the start of EWS and at the end of the study session. Neither unsafe ventilator settings nor failure of the system occurred. All patients were successfully transferred from controlled ventilation to assisted spontaneous breathing in a mean time of 37 ± 17 min (± SD). Early settings applied by the EWS did not significantly differ from the initial settings, except for the fraction of oxygen in inspired gas. During the later course, EWS significantly modified most of the ventilator settings and reduced the imposed respiratory load. A novel prototype automated weaning system was successfully developed. The first clinical application of EWS revealed that its operation was stable, safe ventilator settings were defined and the respiratory load of mechanical ventilation was decreased.

  13. Molecular and protein markers for clinical decision making in breast cancer: today and tomorrow.

    Science.gov (United States)

    Harbeck, Nadia; Sotlar, Karl; Wuerstlein, Rachel; Doisneau-Sixou, Sophie

    2014-04-01

    In early breast cancer (eBC), established clinicopathological factors are not sufficient for clinical decision making particularly regarding adjuvant chemotherapy since substantial over- or undertreatment may occur. Thus, novel protein- and molecular markers have been put forward as decision aids. Since these potential prognosis and/or predictive tests differ substantially regarding their methodology, analytical and clinical validation, this review attempts to summarize the essential facts for clinicians. This review focuses on those markers which are the most advanced so far in their development towards routine clinical application, i.e. two protein markers (i.e. uPA/PAI-1 and IHC4) and six molecular multigene tests (i.e. Mammaprint®, Oncotype DX®, PAM50, Endopredict®, the 97-gene genomic grade, and 76 gene Rotterdam signatures). Next to methodological aspects, we summarized the clinical evidences, in particular the main prospective clinical trials which have already been fully recruited (i.e. MINDACT, TAILORx, WSG PLAN B) or are still ongoing (i.e. RxPONDER/SWOG S1007, WSG-ADAPT). Last but not least, this review points out the key elements for clinicians to select one test among the wide panel of proposed assays, for a specific population of patients in term of level of evidence, analytical and clinical validity as well as cost effectiveness. Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Studying the effect of clinical uncertainty on physicians' decision-making using ILIAD.

    Science.gov (United States)

    Anderson, J D; Jay, S J; Weng, H C; Anderson, M M

    1995-01-01

    The influence of uncertainty on physicians' practice behavior is not well understood. In this research, ILIAD, a diagnostic expert system, has been used to study physicians' responses to uncertainty and how their responses affected clinical performance. The simulation mode of ILIAD was used to standardize the presentation and scoring of two cases to 46 residents in emergency medicine, internal medicine, family practice and transitional medicine at Methodist Hospital of Indiana. A questionnaire was used to collect additional data on how physicians respond to clinical uncertainty. A structural equation model was developed, estimated, and tested. The results indicate that stress that physicians experience in dealing with clinical uncertainty has a negative effect on their clinical performance. Moreover, the way that physicians respond to uncertainty has positive and negative effects on their performance. Open discussions with patients about clinical decisions and the use of practice guidelines improves performance. However, when the physician's clinical decisions are influenced by patient demands or their peers, their performance scores decline.

  15. Mapping clinical outcomes expectations to treatment decisions: an application to vestibular schwannoma management.

    Science.gov (United States)

    Cheung, Steven W; Aranda, Derick; Driscoll, Colin L W; Parsa, Andrew T

    2010-02-01

    Complex medical decision making obligates tradeoff assessments among treatment outcomes expectations, but an accessible tool to perform the necessary analysis is conspicuously absent. We aimed to demonstrate methodology and feasibility of adapting conjoint analysis for mapping clinical outcomes expectations to treatment decisions in vestibular schwannoma (VS) management. Prospective. Tertiary medical center and US-based otologists/neurotologists. Treatment preference profiles among VS stakeholders-61 younger and 74 older prospective patients, 61 observation patients, and 60 surgeons-were assessed for the synthetic VS case scenario of a 10-mm tumor in association with useful hearing and normal facial function. Treatment attribute utility. Conjoint analysis attribute levels were set in accordance to the results of a meta-analysis. Forty-five case series were disaggregated to formulate microsurgery facial nerve and hearing preservation outcomes expectations models. Attribute utilities were computed and mapped to the realistic treatment choices of translabyrinthine craniotomy, middle fossa craniotomy, and gamma knife radiosurgery. Among the treatment attributes of likelihoods of causing deafness, temporary facial weakness for 2 months, and incurable cancer within 20 years, and recovery time, permanent deafness was less important to tumor surgeons, and temporary facial weakness was more important to tumor surgeons and observation patients (Wilcoxon rank-sum, p knife radiosurgery. Mapping clinical outcomes expectations to treatment decisions for a synthetic clinical scenario revealed inhomogeneous drivers of choice selection among study cohorts. Medical decision engines that analyze personal preferences of outcomes expectations for VS and many other diseases may be developed to promote shared decision making among health care stakeholders and transparency in the informed consent process.

  16. Factors influencing a nurse's decision to question medication administration in a neonatal clinical care unit.

    Science.gov (United States)

    Aydon, Laurene; Hauck, Yvonne; Zimmer, Margo; Murdoch, Jamee

    2016-09-01

    The aim of this study was to identify factors that influence nurse's decisions to question concerning aspects of medication administration within the context of a neonatal clinical care unit. Medication error in the neonatal setting can be high with this particularly vulnerable population. As the care giver responsible for medication administration, nurses are deemed accountable for most errors. However, they are recognised as the forefront of prevention. Minimal evidence is available around reasoning, decision making and questioning around medication administration. Therefore, this study focuses upon addressing the gap in knowledge around what nurses believe influences their decision to question. A critical incident design was employed where nurses were asked to describe clinical incidents around their decision to question a medication issue. Nurses were recruited from a neonatal clinical care unit and participated in an individual digitally recorded interview. One hundred and three nurses participated between December 2013-August 2014. Use of the constant comparative method revealed commonalities within transcripts. Thirty-six categories were grouped into three major themes: 'Working environment', 'Doing the right thing' and 'Knowledge about medications'. Findings highlight factors that influence nurses' decision to question issues around medication administration. Nurses feel it is their responsibility to do the right thing and speak up for their vulnerable patients to enhance patient safety. Negative dimensions within the themes will inform planning of educational strategies to improve patient safety, whereas positive dimensions must be reinforced within the multidisciplinary team. The working environment must support nurses to question and ultimately provide safe patient care. Clear and up to date policies, formal and informal education, role modelling by senior nurses, effective use of communication skills and a team approach can facilitate nurses to

  17. Automated electrocardiogram interpretation programs versus cardiologists' triage decision making based on teletransmitted data in patients with suspected acute coronary syndrome

    DEFF Research Database (Denmark)

    Clark, Elaine N; Ripa, Maria Sejersten; Clemmensen, Peter

    2010-01-01

    The aims of this study were to assess the effectiveness of 2 automated electrocardiogram interpretation programs in patients with suspected acute coronary syndrome transported to hospital by ambulance in 1 rural region of Denmark with hospital discharge diagnosis used as the gold standard...... infarction with respect to discharge diagnosis were 78%, 91%, and 81% for LIFEPAK 12 and 78%, 94%, and 87% for the Glasgow program. Corresponding data for attending cardiologists were 85%, 90%, and 81%. In conclusion, the Glasgow program had significantly higher specificity than the LIFEPAK 12 program (p = 0...

  18. An engineered approach to stem cell culture: automating the decision process for real-time adaptive subculture of stem cells.

    Directory of Open Access Journals (Sweden)

    Dai Fei Elmer Ker

    Full Text Available Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway, the majority of such systems still require human intervention to determine when to subculture. Thus, it is necessary to accurately and objectively determine the appropriate time for cell passaging. Optimal stem cell culturing that maintains cell pluripotency while maximizing cell yields will be especially important for efficient, cost-effective stem cell-based therapies. Toward this goal we developed a real-time computer vision-based system that monitors the degree of cell confluency with a precision of 0.791±0.031 and recall of 0.559±0.043. The system consists of an automated phase-contrast time-lapse microscope and a server. Multiple dishes are sequentially imaged and the data is uploaded to the server that performs computer vision processing, predicts when cells will exceed a pre-defined threshold for optimal cell confluency, and provides a Web-based interface for remote cell culture monitoring. Human operators are also notified via text messaging and e-mail 4 hours prior to reaching this threshold and immediately upon reaching this threshold. This system was successfully used to direct the expansion of a paradigm stem cell population, C2C12 cells. Computer-directed and human-directed control subcultures required 3 serial cultures to achieve the theoretical target cell yield of 50 million C2C12 cells and showed no difference for myogenic and osteogenic differentiation. This automated vision-based system has potential as a tool toward adaptive real-time control of subculturing, cell culture optimization and quality assurance/quality control, and it could be integrated with current and

  19. Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges.

    Science.gov (United States)

    Baig, Mirza Mansoor; GholamHosseini, Hamid; Moqeem, Aasia A; Mirza, Farhaan; Lindén, Maria

    2017-11-01

    Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians' acceptability, as well as the low impact on the medical professionals' decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.

  20. Decision making and senior management: the implementation of change projects covering clinical management in SUS hospitals.

    Science.gov (United States)

    Pacheco, José Márcio da Cunha; Gomes, Romeu

    2016-08-01

    This paper analyses the decision making process for senior management in public hospitals that are a part of the National Health Service in Brazil (hereafter SUS) in relation to projects aimed at changing clinical management. The methodological design of this study is qualitative in nature taking a hermeneutics-dialectics perspective in terms of results. Hospital directors noted that clinical management projects changed the state of hospitals through: improving their organizations, mobilizing their staff in order to increase a sense of order and systemizing actions and available resources. Technical rationality was the principal basis used in the decision making process for managers. Due to the reality of many hospitals having fragmented organizations, this fact impeded the use of aspects related to rationality, such as economic and financial factors in the decision making process. The incremental model and general politics also play a role in this area. We concluded that the decision making process embraces a large array of factors including rational aspects such as the use of management techniques and the ability to analyze, interpret and summarize. It also incorporates subjective elements such as how to select values and dealing with people's working experiences. We recognized that management problems are wide in scope, ambiguous, complex and do not come with a lot of structure in practice.

  1. Multimorbidity, service organization and clinical decision making in primary care: a qualitative study.

    Science.gov (United States)

    Bower, Peter; Macdonald, Wendy; Harkness, Elaine; Gask, Linda; Kendrick, Tony; Valderas, Jose M; Dickens, Chris; Blakeman, Tom; Sibbald, Bonnie

    2011-10-01

    Primary care professionals often manage patients with multiple long-term health conditions, but managing multimorbidity is challenging given time and resource constraints and interactions between conditions. To explore GP and nurse perceptions of multimorbidity and the influence on service organization and clinical decision making. A qualitative interview study with primary care professionals in practices in Greater Manchester, U.K. Interviews were conducted with 15 GPs and 10 practice nurses. Primary care professionals identified tensions between delivering care to meet quality targets and fulfilling the patient's agenda, tensions which are exacerbated in multimorbidity. They were aware of the inconvenience suffered by patients through attendance at multiple clinic appointments when care was structured around individual conditions. They reported difficulties managing patients with multimorbidity in limited consultation time, which led to adoption of an 'additive-sequential' decision-making model which dealt with problems in priority order until consultation resources were exhausted, when further management was deferred. Other challenges included the need for patients to co-ordinate their care, the difficulties of self-management support in multimorbidity and problems of making sense of the relationships between physical and mental health. Doctor and nurse accounts included limited consideration of multimorbidity in terms of the interactions between conditions or synergies between management of different conditions. Primary care professionals identify a number of challenges in care for multimorbidity and adopt a particular model of decision making to deliver care for multiple individual conditions. However, they did not describe specific decision making around managing multimorbidity per se.

  2. Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study.

    Science.gov (United States)

    Kerlikowske, Karla; Scott, Christopher G; Mahmoudzadeh, Amir P; Ma, Lin; Winham, Stacey; Jensen, Matthew R; Wu, Fang Fang; Malkov, Serghei; Pankratz, V Shane; Cummings, Steven R; Shepherd, John A; Brandt, Kathleen R; Miglioretti, Diana L; Vachon, Celine M

    2018-06-05

    In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead. To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures. Case-control. San Francisco Mammography Registry and Mayo Clinic. 1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants. Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity. Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively. Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method. Automated and clinical BI

  3. Ethnic bias and clinical decision-making among New Zealand medical students: an observational study.

    Science.gov (United States)

    Harris, Ricci; Cormack, Donna; Stanley, James; Curtis, Elana; Jones, Rhys; Lacey, Cameron

    2018-01-23

    Health professional racial/ethnic bias may impact on clinical decision-making and contribute to subsequent ethnic health inequities. However, limited research has been undertaken among medical students. This paper presents findings from the Bias and Decision-Making in Medicine (BDMM) study, which sought to examine ethnic bias (Māori (indigenous peoples) compared with New Zealand European) among medical students and associations with clinical decision-making. All final year New Zealand (NZ) medical students in 2014 and 2015 (n = 888) were invited to participate in a cross-sectional online study. Key components included: two chronic disease vignettes (cardiovascular disease (CVD) and depression) with randomized patient ethnicity (Māori or NZ European) and questions on patient management; implicit bias measures (an ethnicity preference Implicit Association Test (IAT) and an ethnicity and compliant patient IAT); and, explicit ethnic bias questions. Associations between ethnic bias and clinical decision-making responses to vignettes were tested using linear regression. Three hundred and two students participated (34% response rate). Implicit and explicit ethnic bias favoring NZ Europeans was apparent among medical students. In the CVD vignette, no significant differences in clinical decision-making by patient ethnicity were observed. There were also no differential associations by patient ethnicity between any measures of ethnic bias (implicit or explicit) and patient management responses in the CVD vignette. In the depression vignette, some differences in the ranking of recommended treatment options were observed by patient ethnicity and explicit preference for NZ Europeans was associated with increased reporting that NZ European patients would benefit from treatment but not Māori (slope difference 0.34, 95% CI 0.08, 0.60; p = 0.011), although this was the only significant finding in these analyses. NZ medical students demonstrated ethnic bias, although

  4. Unconscious race and social class bias among acute care surgical clinicians and clinical treatment decisions.

    Science.gov (United States)

    Haider, Adil H; Schneider, Eric B; Sriram, N; Dossick, Deborah S; Scott, Valerie K; Swoboda, Sandra M; Losonczy, Lia; Haut, Elliott R; Efron, David T; Pronovost, Peter J; Lipsett, Pamela A; Cornwell, Edward E; MacKenzie, Ellen J; Cooper, Lisa A; Freischlag, Julie A

    2015-05-01

    Significant health inequities persist among minority and socially disadvantaged patients. Better understanding of how unconscious biases affect clinical decision making may help to illuminate clinicians' roles in propagating disparities. To determine whether clinicians' unconscious race and/or social class biases correlate with patient management decisions. We conducted a web-based survey among 230 physicians from surgery and related specialties at an academic, level I trauma center from December 1, 2011, through January 31, 2012. We administered clinical vignettes, each with 3 management questions. Eight vignettes assessed the relationship between unconscious bias and clinical decision making. We performed ordered logistic regression analysis on the Implicit Association Test (IAT) scores and used multivariable analysis to determine whether implicit bias was associated with the vignette responses. Differential response times (D scores) on the IAT as a surrogate for unconscious bias. Patient management vignettes varied by patient race or social class. Resulting D scores were calculated for each management decision. In total, 215 clinicians were included and consisted of 74 attending surgeons, 32 fellows, 86 residents, 19 interns, and 4 physicians with an undetermined level of education. Specialties included surgery (32.1%), anesthesia (18.1%), emergency medicine (18.1%), orthopedics (7.9%), otolaryngology (7.0%), neurosurgery (7.0%), critical care (6.0%), and urology (2.8%); 1.9% did not report a departmental affiliation. Implicit race and social class biases were present in most respondents. Among all clinicians, mean IAT D scores for race and social class were 0.42 (95% CI, 0.37-0.48) and 0.71 (95% CI, 0.65-0.78), respectively. Race and class scores were similar across departments (general surgery, orthopedics, urology, etc), race, or age. Women demonstrated less bias concerning race (mean IAT D score, 0.39 [95% CI, 0.29-0.49]) and social class (mean IAT D score

  5. The anatomy of clinical decision-making in multidisciplinary cancer meetings

    Science.gov (United States)

    Soukup, Tayana; Petrides, Konstantinos V.; Lamb, Benjamin W.; Sarkar, Somita; Arora, Sonal; Shah, Sujay; Darzi, Ara; Green, James S. A.; Sevdalis, Nick

    2016-01-01

    Abstract In the UK, treatment recommendations for patients with cancer are routinely made by multidisciplinary teams in weekly meetings. However, their performance is variable. The aim of this study was to explore the underlying structure of multidisciplinary decision-making process, and examine how it relates to team ability to reach a decision. This is a cross-sectional observational study consisting of 1045 patient reviews across 4 multidisciplinary cancer teams from teaching and community hospitals in London, UK, from 2010 to 2014. Meetings were chaired by surgeons. We used a validated observational instrument (Metric for the Observation of Decision-making in Cancer Multidisciplinary Meetings) consisting of 13 items to assess the decision-making process of each patient discussion. Rated on a 5-point scale, the items measured quality of presented patient information, and contributions to review by individual disciplines. A dichotomous outcome (yes/no) measured team ability to reach a decision. Ratings were submitted to Exploratory Factor Analysis and regression analysis. The exploratory factor analysis produced 4 factors, labeled “Holistic and Clinical inputs” (patient views, psychosocial aspects, patient history, comorbidities, oncologists’, nurses’, and surgeons’ inputs), “Radiology” (radiology results, radiologists’ inputs), “Pathology” (pathology results, pathologists’ inputs), and “Meeting Management” (meeting chairs’ and coordinators’ inputs). A negative cross-loading was observed from surgeons’ input on the fourth factor with a follow-up analysis showing negative correlation (r = −0.19, P < 0.001). In logistic regression, all 4 factors predicted team ability to reach a decision (P < 0.001). Hawthorne effect is the main limitation of the study. The decision-making process in cancer meetings is driven by 4 underlying factors representing the complete patient profile and contributions to case review by all core

  6. Clinical decision making for a tooth with apical periodontitis: the patients' preferred level of participation.

    Science.gov (United States)

    Azarpazhooh, Amir; Dao, Thuan; Ungar, Wendy J; Chaudry, Faiza; Figueiredo, Rafael; Krahn, Murray; Friedman, Shimon

    2014-06-01

    To effectively engage patients in clinical decisions regarding the management of teeth with apical periodontitis (AP), there is a need to explore patients' perspectives on the decision-making process. This study surveyed patients for their preferred level of participation in making treatment decisions for a tooth with AP. Data were collected through a mail-out survey of 800 University of Toronto Faculty of Dentistry patients, complemented by a convenience sample of 200 patients from 10 community practices. The Control Preferences Scale was used to evaluate the patients' preferences for active, collaborative, or passive participation in treatment decisions for a tooth with AP. Using bivariate and logistic regression analyses, the Gelberg-Andersen Behavioral Model for Vulnerable Populations was applied to the Control Preferences Scale questions to understand the influential factors (P ≤ .05). Among 434 of 1,000 respondents, 44%, 40%, and 16% preferred an active, collaborative, and passive participation, respectively. Logistic regression showed a significant association (P ≤ .025) between participants' higher education and preference for active participation compared with a collaborative role. Also, immigrant status was significantly associated with preference for passive participation (P = .025). The majority of patients valued an active or collaborative participation in deciding treatment for a tooth with AP. This pattern implied a preference for a patient-centered practice mode that emphasizes patient autonomy in decision making. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

  7. Medical Device Integrated Vital Signs Monitoring Application with Real-Time Clinical Decision Support.

    Science.gov (United States)

    Moqeem, Aasia; Baig, Mirza; Gholamhosseini, Hamid; Mirza, Farhaan; Lindén, Maria

    2018-01-01

    This research involves the design and development of a novel Android smartphone application for real-time vital signs monitoring and decision support. The proposed application integrates market available, wireless and Bluetooth connected medical devices for collecting vital signs. The medical device data collected by the app includes heart rate, oxygen saturation and electrocardiograph (ECG). The collated data is streamed/displayed on the smartphone in real-time. This application was designed by adopting six screens approach (6S) mobile development framework and focused on user-centered approach and considered clinicians-as-a-user. The clinical engagement, consultations, feedback and usability of the application in the everyday practices were considered critical from the initial phase of the design and development. Furthermore, the proposed application is capable to deliver rich clinical decision support in real-time using the integrated medical device data.

  8. How Qualitative Research Informs Clinical and Policy Decision Making in Transplantation: A Review.

    Science.gov (United States)

    Tong, Allison; Morton, Rachael L; Webster, Angela C

    2016-09-01

    Patient-centered care is no longer just a buzzword. It is now widely touted as a cornerstone in delivering quality care across all fields of medicine. However, patient-centered strategies and interventions necessitate evidence about patients' decision-making processes, values, priorities, and needs. Qualitative research is particularly well suited to understanding the experience and perspective of patients, donors, clinicians, and policy makers on a wide range of transplantation-related topics including organ donation and allocation, adherence to prescribed therapy, pretransplant and posttransplant care, implementation of clinical guidelines, and doctor-patient communication. In transplantation, evidence derived from qualitative research has been integrated into strategies for shared decision-making, patient educational resources, process evaluations of trials, clinical guidelines, and policies. The aim of this article is to outline key concepts and methods used in qualitative research, guide the appraisal of qualitative studies, and assist clinicians to understand how qualitative research may inform their practice and policy.

  9. The utility of observational studies in clinical decision making: lessons learned from statin trials.

    Science.gov (United States)

    Foody, JoAnne M; Mendys, Phillip M; Liu, Larry Z; Simpson, Ross J

    2010-05-01

    Contemporary clinical decision making is well supported by a wide variety of information sources, including clinical practice guidelines, position papers, and insights from randomized controlled trials (RCTs). Much of our fundamental understanding of cardiovascular risk factors is based on multiple observations from major epidemiologic studies, such as The Seven Country Studies and the US-based Framingham Heart Study. These studies provided the framework for the development of clinical practice guidelines, including the National Cholesterol Education Program Adult Treatment Panel series. The objective of this article is to highlight the value of observational studies as a complement to clinical trial data for clinical decision making in real-world practice. Although RCTs are still the benchmark for assessing clinical efficacy and safety of a specific therapeutic approach, they may be of limited utility to practitioners who must then adapt the lessons learned from the trial into the patient care environment. The use of well-structured observational studies can improve our understanding of the translation of clinical trials into clinical practice, as demonstrated here with the example of statins. Although such studies have their own limitations, improved techniques for design and analysis have reduced the impact of bias and confounders. The introduction of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines has provided more uniformity for such studies. When used together with RCTs, observational studies can enhance our understanding of effectiveness and utility in real-world clinical practice. In the examples of statin observational studies, the results suggest that relative effectiveness of different statins and potential impact of switching statins should be carefully considered in treating individual patients by practicing physicians.

  10. Development of traditional Chinese medicine clinical data warehouse for medical knowledge discovery and decision support.

    Science.gov (United States)

    Zhou, Xuezhong; Chen, Shibo; Liu, Baoyan; Zhang, Runsun; Wang, Yinghui; Li, Ping; Guo, Yufeng; Zhang, Hua; Gao, Zhuye; Yan, Xiufeng

    2010-01-01

    Traditional Chinese medicine (TCM) is a scientific discipline, which develops the related theories from the long-term clinical practices. The large-scale clinical data are the core empirical knowledge source for TCM research. This paper introduces a clinical data warehouse (CDW) system, which incorporates the structured electronic medical record (SEMR) data for medical knowledge discovery and TCM clinical decision support (CDS). We have developed the clinical reference information model (RIM) and physical data model to manage the various information entities and their relationships in TCM clinical data. An extraction-transformation-loading (ETL) tool is implemented to integrate and normalize the clinical data from different operational data sources. The CDW includes online analytical processing (OLAP) and complex network analysis (CNA) components to explore the various clinical relationships. Furthermore, the data mining and CNA methods are used to discover the valuable clinical knowledge from the data. The CDW has integrated 20,000 TCM inpatient data and 20,000 outpatient data, which contains manifestations (e.g. symptoms, physical examinations and laboratory test results), diagnoses and prescriptions as the main information components. We propose a practical solution to accomplish the large-scale clinical data integration and preprocessing tasks. Meanwhile, we have developed over 400 OLAP reports to enable the multidimensional analysis of clinical data and the case-based CDS. We have successfully conducted several interesting data mining applications. Particularly, we use various classification methods, namely support vector machine, decision tree and Bayesian network, to discover the knowledge of syndrome differentiation. Furthermore, we have applied association rule and CNA to extract the useful acupuncture point and herb combination patterns from the clinical prescriptions. A CDW system consisting of TCM clinical RIM, ETL, OLAP and data mining as the core

  11. Access to augmentative and alternative communication: new technologies and clinical decision-making.

    Science.gov (United States)

    Fager, Susan; Bardach, Lisa; Russell, Susanne; Higginbotham, Jeff

    2012-01-01

    Children with severe physical impairments require a variety of access options to augmentative and alternative communication (AAC) and computer technology. Access technologies have continued to develop, allowing children with severe motor control impairments greater independence and access to communication. This article will highlight new advances in access technology, including eye and head tracking, scanning, and access to mainstream technology, as well as discuss future advances. Considerations for clinical decision-making and implementation of these technologies will be presented along with case illustrations.

  12. A Serious Game for Teaching Nursing Students Clinical Reasoning and Decision-Making Skills.

    Science.gov (United States)

    Johnsen, Hege Mari; Fossum, Mariann; Vivekananda-Schmidt, Pirashanthie; Fruhling, Ann; Slettebø, Åshild

    2016-01-01

    The aim of this study was to design and pilot-test a serious game for teaching nursing students clinical reasoning and decision-making skills in caring for patients with chronic obstructive pulmonary disease. A video-based serious game prototype was developed. A purposeful sample of six participants tested and evaluated the prototype. Usability issues were identified regarding functionality and user-computer interface. However, overall the serious game was perceived to be useful, usable and likable to use.

  13. Physicians' perspectives on communication and decision making in clinical encounters for treatment of latent tuberculosis infection

    OpenAIRE

    Claudia C. Dobler; Sinthia Bosnic-Anticevich; Carol L. Armour

    2018-01-01

    The aim of the study was to explore the views of tuberculosis (TB) physicians on treatment of latent TB infection (LTBI), focusing on decision making and communication in clinical practice. 20 Australian TB physicians participated in a semistructured interview in person or over the telephone. Interviews were recorded, transcribed and analysed thematically. The study identified challenges that physicians face when discussing treatment for LTBI with patients. These included difficulties explain...

  14. EHRs Connect Research and Practice: Where Predictive Modeling, Artificial Intelligence, and Clinical Decision Support Intersect

    OpenAIRE

    Bennett, Casey; Doub, Tom; Selove, Rebecca

    2012-01-01

    Objectives: Electronic health records (EHRs) are only a first step in capturing and utilizing health-related data - the challenge is turning that data into useful information. Furthermore, EHRs are increasingly likely to include data relating to patient outcomes, functionality such as clinical decision support, and genetic information as well, and, as such, can be seen as repositories of increasingly valuable information about patients' health conditions and responses to treatment over time. ...

  15. Designing a Clinical Framework to Guide Gross Motor Intervention Decisions for Infants and Young Children with Hypotonia

    Science.gov (United States)

    Darrah, Johanna; O'Donnell, Maureen; Lam, Joyce; Story, Maureen; Wickenheiser, Diane; Xu, Kaishou; Jin, Xiaokun

    2013-01-01

    Clinical practice frameworks are a valuable component of clinical education, promoting informed clinical decision making based on the best available evidence and/or clinical experience. They encourage standardized intervention approaches and evaluation of practice. Based on an international project to support the development of an enhanced service…

  16. Automated classification of eligibility criteria in clinical trials to facilitate patient-trial matching for specific patient populations.

    Science.gov (United States)

    Zhang, Kevin; Demner-Fushman, Dina

    2017-07-01

    To develop automated classification methods for eligibility criteria in ClinicalTrials.gov to facilitate patient-trial matching for specific populations such as persons living with HIV or pregnant women. We annotated 891 interventional cancer trials from ClinicalTrials.gov based on their eligibility for human immunodeficiency virus (HIV)-positive patients using their eligibility criteria. These annotations were used to develop classifiers based on regular expressions and machine learning (ML). After evaluating classification of cancer trials for eligibility of HIV-positive patients, we sought to evaluate the generalizability of our approach to more general diseases and conditions. We annotated the eligibility criteria for 1570 of the most recent interventional trials from ClinicalTrials.gov for HIV-positive and pregnancy eligibility, and the classifiers were retrained and reevaluated using these data. On the cancer-HIV dataset, the baseline regex model, the bag-of-words ML classifier, and the ML classifier with named entity recognition (NER) achieved macro-averaged F2 scores of 0.77, 0.87, and 0.87, respectively; the addition of NER did not result in a significant performance improvement. On the general dataset, ML + NER achieved macro-averaged F2 scores of 0.91 and 0.85 for HIV and pregnancy, respectively. The eligibility status of specific patient populations, such as persons living with HIV and pregnant women, for clinical trials is of interest to both patients and clinicians. We show that it is feasible to develop a high-performing, automated trial classification system for eligibility status that can be integrated into consumer-facing search engines as well as patient-trial matching systems. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the US.

  17. Clinical decision-making: heuristics and cognitive biases for the ophthalmologist.

    Science.gov (United States)

    Hussain, Ahsen; Oestreicher, James

    Diagnostic errors have a significant impact on health care outcomes and patient care. The underlying causes and development of diagnostic error are complex with flaws in health care systems, as well as human error, playing a role. Cognitive biases and a failure of decision-making shortcuts (heuristics) are human factors that can compromise the diagnostic process. We describe these mechanisms, their role with the clinician, and provide clinical scenarios to highlight the various points at which biases may emerge. We discuss strategies to modify the development and influence of these processes and the vulnerability of heuristics to provide insight and improve clinical outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. A programmable rules engine to provide clinical decision support using HTML forms.

    Science.gov (United States)

    Heusinkveld, J; Geissbuhler, A; Sheshelidze, D; Miller, R

    1999-01-01

    The authors have developed a simple method for specifying rules to be applied to information on HTML forms. This approach allows clinical experts, who lack the programming expertise needed to write CGI scripts, to construct and maintain domain-specific knowledge and ordering capabilities within WizOrder, the order-entry and decision support system used at Vanderbilt Hospital. The clinical knowledge base maintainers use HTML editors to create forms and spreadsheet programs for rule entry. A test environment has been developed which uses Netscape to display forms; the production environment displays forms using an embedded browser.

  19. Can a patient smart card improve decision making in a clinical setting?.

    Science.gov (United States)

    Bérubé, J; Papillon, M J; Lavoie, G; Durant, P; Fortin, J P

    1995-01-01

    In the health field, clinical information is the raw material for the clinician delivering health services. Therefore, the clinical information available to the physician is often incomplete or even non¿existent upon consultation. Furthermore, the reconstruction of the medical history, which is the most important source of data for the clinician to establish a diagnosis and initiate a treatment, suffers from many constraints. The smart card, like the one used in Quebec's project, could ease the physician's decision-making by allowing fast access to accurate and pertinent data. The smart card is a major asset in the present health system.

  20. Trail Blazing or Jam Session? Towards a new Concept of Clinical Decision-Making

    OpenAIRE

    Risør, Torsten

    2016-01-01

    Manuscript. Published version available at http://dx.doi.org/10.1080/13648470.2016.1239695 Clinical decision-making (CDM) is key in learning to be a doctor as the defining activity in their clinical work. CDM is often portrayed in the literature as similar to ‘trail blazing’; the doctor as the core agent, clearing away obstacles on the path towards diagnosis and treatment. However, in a fieldwork of young doctors in Denmark, it was difficult connect their practice to this image....

  1. Mock Pages Are a Valid Construct for Assessment of Clinical Decision Making and Interprofessional Communication.

    Science.gov (United States)

    Boehler, Margaret L; Schwind, Cathy J; Markwell, Stephen J; Minter, Rebecca M

    2017-01-01

    Answering pages from nurses about patients in need of immediate attention is one of the most difficult challenges a resident faces during their first days as a physician. A Mock Page program has been developed and adopted into a national surgical resident preparatory curriculum to prepare senior medical students for this important skill. The purpose of this study is to assess standardized mock page cases as a valid construct to assess clinical decision making and interprofessional communication skills. Mock page cases (n = 16) were administered to 213 senior medical students from 12 medical schools participating in a national surgical resident preparatory curriculum in 2013 and 2014. Clinical decision making and interprofessional communication were measured by case-specific assessments evaluating these skills which have undergone rigorous standard-setting to determine pass/fail cut points. Students' performance improved in general for both communication and clinical decision making over the 4-week course. Cases have been identified that seem to be best suited for differentiating high- from low-performing students. Chest pain, pulmonary embolus, and mental status change cases posed the greatest difficulty for student learners. Simulated mock pages demonstrate an innovative technique for training students in both effective interprofessional communication and management of common postoperative conditions they will encounter as new surgical interns.

  2. The potential of predictive analytics to provide clinical decision support in depression treatment planning.

    Science.gov (United States)

    Kessler, Ronald C

    2018-01-01

    To review progress developing clinical decision support tools for personalized treatment of major depressive disorder (MDD). Over the years, a variety of individual indicators ranging from biomarkers to clinical observations and self-report scales have been used to predict various aspects of differential MDD treatment response. Most of this work focused on predicting remission either with antidepressant medications versus psychotherapy, some antidepressant medications versus others, some psychotherapies versus others, and combination therapies versus monotherapies. However, to date, none of the individual predictors in these studies has been strong enough to guide optimal treatment selection for most patients. Interest consequently turned to decision support tools made up of multiple predictors, but the development of such tools has been hampered by small study sample sizes. Design recommendations are made here for future studies to address this problem. Recommendations include using large prospective observational studies followed by pragmatic trials rather than smaller, expensive controlled treatment trials for preliminary development of decision support tools; basing these tools on comprehensive batteries of inexpensive self-report and clinical predictors (e.g., self-administered performance-based neurocognitive tests) versus expensive biomarkers; and reserving biomarker assessments for targeted studies of patients not well classified by inexpensive predictor batteries.

  3. PCA safety data review after clinical decision support and smart pump technology implementation.

    Science.gov (United States)

    Prewitt, Judy; Schneider, Susan; Horvath, Monica; Hammond, Julia; Jackson, Jason; Ginsberg, Brian

    2013-06-01

    Medication errors account for 20% of medical errors in the United States with the largest risk at prescribing and administration. Analgesics or opioids are frequently used medications that can be associated with patient harm when prescribed or administered improperly. In an effort to decrease medication errors, Duke University Hospital implemented clinical decision support via computer provider order entry (CPOE) and "smart pump" technology, 2/2008, with the goal to decrease patient-controlled analgesia (PCA) adverse events. This project evaluated PCA safety events, reviewing voluntary report system and adverse drug events via surveillance (ADE-S), on intermediate and step-down units preimplementation and postimplementation of clinical decision support via CPOE and PCA smart pumps for the prescribing and administration of opioids therapy in the adult patient requiring analgesia for acute pain. Voluntary report system and ADE-S PCA events decreased based upon 1000 PCA days; ADE-S PCA events per 1000 PCA days decreased 22%, from 5.3 (pre) to 4.2 (post) (P = 0.09). Voluntary report system events decreased 72%, from 2.4/1000 PCA days (pre) to 0.66/1000 PCA days (post) and was statistically significant (P PCA events between time periods in both the ADE-S and voluntary report system data, thus supporting the recommendation of clinical decision support via CPOE and PCA smart pump technology.

  4. Privacy-preserving clinical decision support system using Gaussian kernel-based classification.

    Science.gov (United States)

    Rahulamathavan, Yogachandran; Veluru, Suresh; Phan, Raphael C-W; Chambers, Jonathon A; Rajarajan, Muttukrishnan

    2014-01-01

    A clinical decision support system forms a critical capability to link health observations with health knowledge to influence choices by clinicians for improved healthcare. Recent trends toward remote outsourcing can be exploited to provide efficient and accurate clinical decision support in healthcare. In this scenario, clinicians can use the health knowledge located in remote servers via the Internet to diagnose their patients. However, the fact that these servers are third party and therefore potentially not fully trusted raises possible privacy concerns. In this paper, we propose a novel privacy-preserving protocol for a clinical decision support system where the patients' data always remain in an encrypted form during the diagnosis process. Hence, the server involved in the diagnosis process is not able to learn any extra knowledge about the patient's data and results. Our experimental results on popular medical datasets from UCI-database demonstrate that the accuracy of the proposed protocol is up to 97.21% and the privacy of patient data is not compromised.

  5. Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems

    Science.gov (United States)

    Menychtas, Andreas; Tsanakas, Panayiotis

    2016-01-01

    The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging. PMID:27222731

  6. Automated integration of wireless biosignal collection devices for patient-centred decision-making in point-of-care systems.

    Science.gov (United States)

    Menychtas, Andreas; Tsanakas, Panayiotis; Maglogiannis, Ilias

    2016-03-01

    The proper acquisition of biosignals data from various biosensor devices and their remote accessibility are still issues that prevent the wide adoption of point-of-care systems in the routine of monitoring chronic patients. This Letter presents an advanced framework for enabling patient monitoring that utilises a cloud computing infrastructure for data management and analysis. The framework introduces also a local mechanism for uniform biosignals collection from wearables and biosignal sensors, and decision support modules, in order to enable prompt and essential decisions. A prototype smartphone application and the related cloud modules have been implemented for demonstrating the value of the proposed framework. Initial results regarding the performance of the system and the effectiveness in data management and decision-making have been quite encouraging.

  7. Retention payoff-based cost per day open regression equations: Application in a user-friendly decision support tool for investment analysis of automated estrus detection technologies.

    Science.gov (United States)

    Dolecheck, K A; Heersche, G; Bewley, J M

    2016-12-01

    Assessing the economic implications of investing in automated estrus detection (AED) technologies can be overwhelming for dairy producers. The objectives of this study were to develop new regression equations for estimating the cost per day open (DO) and to apply the results to create a user-friendly, partial budget, decision support tool for investment analysis of AED technologies. In the resulting decision support tool, the end user can adjust herd-specific inputs regarding general management, current reproductive management strategies, and the proposed AED system. Outputs include expected DO, reproductive cull rate, net present value, and payback period for the proposed AED system. Utility of the decision support tool was demonstrated with an example dairy herd created using data from DairyMetrics (Dairy Records Management Systems, Raleigh, NC), Food and Agricultural Policy Research Institute (Columbia, MO), and published literature. Resulting herd size, rolling herd average milk production, milk price, and feed cost were 323 cows, 10,758kg, $0.41/kg, and $0.20/kg of dry matter, respectively. Automated estrus detection technologies with 2 levels of initial system cost (low: $5,000 vs. high: $10,000), tag price (low: $50 vs. high: $100), and estrus detection rate (low: 60% vs. high: 80%) were compared over a 7-yr investment period. Four scenarios were considered in a demonstration of the investment analysis tool: (1) a herd using 100% visual observation for estrus detection before adopting 100% AED, (2) a herd using 100% visual observation before adopting 75% AED and 25% visual observation, (3) a herd using 100% timed artificial insemination (TAI) before adopting 100% AED, and (4) a herd using 100% TAI before adopting 75% AED and 25% TAI. Net present value in scenarios 1 and 2 was always positive, indicating a positive investment situation. Net present value in scenarios 3 and 4 was always positive in combinations using a $50 tag price, and in scenario 4, the $5

  8. A First Step towards a Clinical Decision Support System for Post-traumatic Stress Disorders.

    Science.gov (United States)

    Ma, Sisi; Galatzer-Levy, Isaac R; Wang, Xuya; Fenyö, David; Shalev, Arieh Y

    2016-01-01

    PTSD is distressful and debilitating, following a non-remitting course in about 10% to 20% of trauma survivors. Numerous risk indicators of PTSD have been identified, but individual level prediction remains elusive. As an effort to bridge the gap between scientific discovery and practical application, we designed and implemented a clinical decision support pipeline to provide clinically relevant recommendation for trauma survivors. To meet the specific challenge of early prediction, this work uses data obtained within ten days of a traumatic event. The pipeline creates personalized predictive model for each individual, and computes quality metrics for each predictive model. Clinical recommendations are made based on both the prediction of the model and its quality, thus avoiding making potentially detrimental recommendations based on insufficient information or suboptimal model. The current pipeline outperforms the acute stress disorder, a commonly used clinical risk factor for PTSD development, both in terms of sensitivity and specificity.

  9. Interoperability of clinical decision-support systems and electronic health records using archetypes: a case study in clinical trial eligibility.

    Science.gov (United States)

    Marcos, Mar; Maldonado, Jose A; Martínez-Salvador, Begoña; Boscá, Diego; Robles, Montserrat

    2013-08-01

    Clinical decision-support systems (CDSSs) comprise systems as diverse as sophisticated platforms to store and manage clinical data, tools to alert clinicians of problematic situations, or decision-making tools to assist clinicians. Irrespective of the kind of decision-support task CDSSs should be smoothly integrated within the clinical information system, interacting with other components, in particular with the electronic health record (EHR). However, despite decades of developments, most CDSSs lack interoperability features. We deal with the interoperability problem of CDSSs and EHRs by exploiting the dual-model methodology. This methodology distinguishes a reference model and archetypes. A reference model is represented by a stable and small object-oriented model that describes the generic properties of health record information. For their part, archetypes are reusable and domain-specific definitions of clinical concepts in the form of structured and constrained combinations of the entities of the reference model. We rely on archetypes to make the CDSS compatible with EHRs from different institutions. Concretely, we use archetypes for modelling the clinical concepts that the CDSS requires, in conjunction with a series of knowledge-intensive mappings relating the archetypes to the data sources (EHR and/or other archetypes) they depend on. We introduce a comprehensive approach, including a set of tools as well as methodological guidelines, to deal with the interoperability of CDSSs and EHRs based on archetypes. Archetypes are used to build a conceptual layer of the kind of a virtual health record (VHR) over the EHR whose contents need to be integrated and used in the CDSS, associating them with structural and terminology-based semantics. Subsequently, the archetypes are mapped to the EHR by means of an expressive mapping language and specific-purpose tools. We also describe a case study where the tools and methodology have been employed in a CDSS to support

  10. A Qualitative Study of the Influences on Clinical Academic Physicians' Postdoctoral Career Decision-Making.

    Science.gov (United States)

    Ranieri, Veronica F; Barratt, Helen; Rees, Geraint; Fulop, Naomi J

    2018-01-23

    To describe the influences on clinical academic physicians' postdoctoral career decision-making. Thirty-five doctoral trainee physicians from University College London took part in semi-structured interviews in 2015 and 2016. Participants were asked open-ended questions about their career to-date, their experiences undertaking a PhD, and their career plans post-PhD. The interviews were audio-recorded and transcribed. Thematic analysis was used to generate, review, and define themes from the transcripts. Emerging differences and similarities in participants' reasons for pursuing a PhD were then grouped to produce typologies to explore how their experiences influenced their career decision-making. Participants described four key reasons for undertaking a PhD, which formed the basis of the four typologies identified. These reasons included: to pursue a clinical academic career; to complete an extensive period of research to understand whether a clinical academic career was the desired path forward; to improve clinical career prospects; and to take a break from clinical training. These findings highlight the need to target efforts at retaining clinical academic physicians according to their reasons for pursuing a PhD and their subsequent experiences with the process. Those responsible for overseeing clinical training must be well-informed of the long-term benefits of training academically-qualified physicians. In light of current political uncertainty, universities, hospitals, and external agencies alike must increase their efforts to inspire and assuage early-career clinical academic physicians' fears regarding their academic future.This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

  11. Automated processing integrated with a microflow cytometer for pathogen detection in clinical matrices.

    Science.gov (United States)

    Golden, J P; Verbarg, J; Howell, P B; Shriver-Lake, L C; Ligler, F S

    2013-02-15

    A spinning magnetic trap (MagTrap) for automated sample processing was integrated with a microflow cytometer capable of simultaneously detecting multiple targets to provide an automated sample-to-answer diagnosis in 40 min. After target capture on fluorescently coded magnetic microspheres, the magnetic trap automatically concentrated the fluorescently coded microspheres, separated the captured target from the sample matrix, and exposed the bound target sequentially to biotinylated tracer molecules and streptavidin-labeled phycoerythrin. The concentrated microspheres were then hydrodynamically focused in a microflow cytometer capable of 4-color analysis (two wavelengths for microsphere identification, one for light scatter to discriminate single microspheres and one for phycoerythrin bound to the target). A three-fold decrease in sample preparation time and an improved detection limit, independent of target preconcentration, was demonstrated for detection of Escherichia coli 0157:H7 using the MagTrap as compared to manual processing. Simultaneous analysis of positive and negative controls, along with the assay reagents specific for the target, was used to obtain dose-response curves, demonstrating the potential for quantification of pathogen load in buffer and serum. Published by Elsevier B.V.

  12. Barriers and decisions when answering clinical questions at the point of care: a grounded theory study.

    Science.gov (United States)

    Cook, David A; Sorensen, Kristi J; Wilkinson, John M; Berger, Richard A

    2013-11-25

    Answering clinical questions affects patient-care decisions and is important to continuous professional development. The process of point-of-care learning is incompletely understood. To understand what barriers and enabling factors influence physician point-of-care learning and what decisions physicians face during this process. Focus groups with grounded theory analysis. Focus group discussions were transcribed and then analyzed using a constant comparative approach to identify barriers, enabling factors, and key decisions related to physician information-seeking activities. Academic medical center and outlying community sites. Purposive sample of 50 primary care and subspecialist internal medicine and family medicine physicians, interviewed in 11 focus groups. Insufficient time was the main barrier to point-of-care learning. Other barriers included the patient comorbidities and contexts, the volume of available information, not knowing which resource to search, doubt that the search would yield an answer, difficulty remembering questions for later study, and inconvenient access to computers. Key decisions were whether to search (reasons to search included infrequently seen conditions, practice updates, complex questions, and patient education), when to search (before, during, or after the clinical encounter), where to search (with the patient present or in a separate room), what type of resource to use (colleague or computer), what specific resource to use (influenced first by efficiency and second by credibility), and when to stop. Participants noted that key features of efficiency (completeness, brevity, and searchability) are often in conflict. Physicians perceive that insufficient time is the greatest barrier to point-of-care learning, and efficiency is the most important determinant in selecting an information source. Designing knowledge resources and systems to target key decisions may improve learning and patient care.

  13. Professional autonomy in 21st century healthcare: nurses' accounts of clinical decision-making.

    Science.gov (United States)

    Traynor, Michael; Boland, Maggie; Buus, Niels

    2010-10-01

    Autonomy in decision-making has traditionally been described as a feature of professional work, however the work of healthcare professionals has been seen as steadily encroached upon by State and managerialist forces. Nursing has faced particular problems in establishing itself as a credible profession for reasons including history, gender and a traditional subservience to medicine. This paper reports on a focus group study of UK nurses participating in post-qualifying professional development in 2008. Three groups of nurses in different specialist areas comprised a total of 26 participants. The study uses accounts of decision-making to gain insight into contemporary professional nursing. The study also aims to explore the usefulness of a theory of professional work set out by Jamous and Peloille (1970). The analysis draws on notions of interpretive repertoires and elements of narrative analysis. We identified two interpretive repertoires: 'clinical judgement' which was used to describe the different grounds for making judgements; and 'decision-making' which was used to describe organisational circumstances influencing decision-making. Jamous and Peloille's theory proved useful for interpreting instances where the nurses collectively withdrew from the potential dangers of too extreme claims for technicality or indeterminacy in their work. However, their theory did not explain the full range of accounts of decision-making that were given. Taken at face value, the accounts from the participants depict nurses as sometimes practising in indirect ways in order to have influence in the clinical and bureaucratic setting. However, a focus on language use and in particular, interpretive repertoires, has enabled us to suggest that despite an overall picture of severely limited autonomy, nurses in the groups reproduced stories of the successful accomplishment of moral and influential action. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Reproductive Ethics in Commercial Surrogacy: Decision-Making in IVF Clinics in New Delhi, India.

    Science.gov (United States)

    Tanderup, Malene; Reddy, Sunita; Patel, Tulsi; Nielsen, Birgitte Bruun

    2015-09-01

    As a neo-liberal economy, India has become one of the new health tourism destinations, with commercial gestational surrogacy as an expanding market. Yet the Indian Assisted Reproductive Technology (ART) Bill has been pending for five years, and the guidelines issued by the Indian Council of Medical Research are somewhat vague and contradictory, resulting in self-regulated practices of fertility clinics. This paper broadly looks at clinical ethics in reproduction in the practice of surrogacy and decision-making in various procedures. Through empirical research in New Delhi, the capital of India, from December 2011 to November 2012, issues of decision-making on embryo transfer, fetal reduction, and mode of delivery were identified. Interviews were carried out with doctors in eighteen ART clinics, agents from four agencies, and fourteen surrogates. In aiming to fulfil the commissioning parents' demands, doctors were willing to go to the greatest extent possible in their medical practice. Autonomy and decision-making regarding choice of the number of embryos to transfer and the mode of delivery lay neither with commissioning parents nor surrogate mothers but mostly with doctors. In order to ensure higher success rates, surrogates faced the risk of multiple pregnancy and fetal reduction with little information regarding the risks involved. In the globalized market of commercial surrogacy in India, and with clinics compromising on ethics, there is an urgent need for formulation of regulative law for the clinical practice and maintenance of principles of reproductive ethics in order to ensure that the interests of surrogate mothers are safeguarded.

  15. Virtual clinics in glaucoma care: face-to-face versus remote decision-making.

    Science.gov (United States)

    Clarke, Jonathan; Puertas, Renata; Kotecha, Aachal; Foster, Paul J; Barton, Keith

    2017-07-01

    To examine the agreement in clinical decisions of glaucoma status made in a virtual glaucoma clinic with those made during a face-to-face consultation. A trained nurse and technicians entered data prospectively for 204 patients into a proforma. A subsequent face-to-face clinical assessment was completed by either a glaucoma consultant or fellow. Proformas were reviewed remotely by one of two additional glaucoma consultants, and 12 months later, by the clinicians who had undertaken the original clinical examination. The interobserver and intraobserver decision-making agreements of virtual assessment versus standard care were calculated. We identified adverse disagreement between face-to-face and virtual review in 7/204 (3.4%, 95% CI 0.9% to 5.9%) patients, where virtual review failed to predict a need to accelerated follow-up identified in face-to-face review. Misclassification events were rare, occurring in 1.9% (95% CI 0.3% to 3.8%) of assessments. Interobserver κ (95% CI) showed only fair agreement (0.24 (0.04 to 0.43)); this improved to moderate agreement when only consultant decisions were compared against each other (κ=0.41 (0.16 to 0.65)). The intraobserver agreement κ (95% CI) for the consultant was 0.274 (0.073 to 0.476), and that for the fellow was 0.264 (0.031 to 0.497). The low rate of adverse misclassification, combined with the slowly progressive nature of most glaucoma, and the fact that patients will all be regularly reassessed, suggests that virtual clinics offer a safe, logistically viable option for selected patients with glaucoma. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  16. Analysis of Nursing Clinical Decision Support Requests and Strategic Plan in a Large Academic Health System.

    Science.gov (United States)

    Whalen, Kimberly; Bavuso, Karen; Bouyer-Ferullo, Sharon; Goldsmith, Denise; Fairbanks, Amanda; Gesner, Emily; Lagor, Charles; Collins, Sarah

    2016-01-01

    To understand requests for nursing Clinical Decision Support (CDS) interventions at a large integrated health system undergoing vendor-based EHR implementation. In addition, to establish a process to guide both short-term implementation and long-term strategic goals to meet nursing CDS needs. We conducted an environmental scan to understand current state of nursing CDS over three months. The environmental scan consisted of a literature review and an analysis of CDS requests received from across our health system. We identified existing high priority CDS and paper-based tools used in nursing practice at our health system that guide decision-making. A total of 46 nursing CDS requests were received. Fifty-six percent (n=26) were specific to a clinical specialty; 22 percent (n=10) were focused on facilitating clinical consults in the inpatient setting. "Risk Assessments/Risk Reduction/Promotion of Healthy Habits" (n=23) was the most requested High Priority Category received for nursing CDS. A continuum of types of nursing CDS needs emerged using the Data-Information-Knowledge-Wisdom Conceptual Framework: 1) facilitating data capture, 2) meeting information needs, 3) guiding knowledge-based decision making, and 4) exposing analytics for wisdom-based clinical interpretation by the nurse. Identifying and prioritizing paper-based tools that can be modified into electronic CDS is a challenge. CDS strategy is an evolving process that relies on close collaboration and engagement with clinical sites for short-term implementation and should be incorporated into a long-term strategic plan that can be optimized and achieved overtime. The Data-Information-Knowledge-Wisdom Conceptual Framework in conjunction with the High Priority Categories established may be a useful tool to guide a strategic approach for meeting short-term nursing CDS needs and aligning with the organizational strategic plan.

  17. Preliminary clinical evaluation of semi-automated nailfold capillaroscopy in the assessment of patients with Raynaud's phenomenon.

    Science.gov (United States)

    Murray, Andrea K; Feng, Kaiyan; Moore, Tonia L; Allen, Phillip D; Taylor, Christopher J; Herrick, Ariane L

    2011-08-01

      Nailfold capillaroscopy is well established in screening patients with Raynaud's phenomenon for underlying SSc-spectrum disorders, by identifying abnormal capillaries. Our aim was to compare semi-automatic feature measurement from newly developed software with manual measurements, and determine the degree to which semi-automated data allows disease group classification.   Images from 46 healthy controls, 21 patients with PRP and 49 with SSc were preprocessed, and semi-automated measurements of intercapillary distance and capillary width, tortuosity, and derangement were performed. These were compared with manual measurements. Features were used to classify images into the three subject groups.   Comparison of automatic and manual measures for distance, width, tortuosity, and derangement had correlations of r=0.583, 0.624, 0.495 (p<0.001), and 0.195 (p=0.040). For automatic measures, correlations were found between width and intercapillary distance, r=0.374, and width and tortuosity, r=0.573 (p<0.001). Significant differences between subject groups were found for all features (p<0.002). Overall, 75% of images correctly matched clinical classification using semi-automated features, compared with 71% for manual measurements.   Semi-automatic and manual measurements of distance, width, and tortuosity showed moderate (but statistically significant) correlations. Correlation for derangement was weaker. Semi-automatic measurements are faster than manual measurements. Semi-automatic parameters identify differences between groups, and are as good as manual measurements for between-group classification. © 2011 John Wiley & Sons Ltd.

  18. A pilot clinical trial on a Variable Automated Speed and Sensing Treadmill (VASST) for hemiparetic gait rehabilitation in stroke patients.

    Science.gov (United States)

    Chua, Karen S G; Chee, Johnny; Wong, Chin J; Lim, Pang H; Lim, Wei S; Hoo, Chuan M; Ong, Wai S; Shen, Mira L; Yu, Wei S

    2015-01-01

    Impairments in walking speed and capacity are common problems after stroke which may benefit from treadmill training. However, standard treadmills, are unable to adapt to the slower walking speeds of stroke survivors and are unable to automate training progression. This study tests a Variable Automated Speed and Sensing Treadmill (VASST) using a standard clinical protocol. VASST is a semi-automated treadmill with multiple sensors and micro controllers, including wireless control to reposition a fall-prevention harness, variable pre-programmed exercise parameters and laser beam foot sensors positioned on the belt to detect subject's foot positions. An open-label study with assessor blinding was conducted in 10 community-dwelling chronic hemiplegic patients who could ambulate at least 0.1 m/s. Interventions included physiotherapist-supervised training on VASST for 60 min three times per week for 4 weeks (total 12 h). Outcome measures of gait speed, quantity, balance, and adverse events were assessed at baseline, 2, 4, and 8 weeks. Ten subjects (8 males, mean age 55.5 years, 2.1 years post stroke) completed VASST training. Mean 10-m walk test speed was 0.69 m/s (SD = 0.29) and mean 6-min walk test distance was 178.3 m (84.0). After 4 weeks of training, 70% had significant positive gains in gait speed (0.06 m/s, SD = 0.08 m/s, P = 0.037); and 90% improved in walking distance. (54.3 m, SD = 30.9 m, P = 0.005). There were no adverse events. This preliminary study demonstrates the initial feasibility and short-term efficacy of VASST for walking speed and distance for people with chronic post-stroke hemiplegia.

  19. Formative Evaluation of Clinician Experience with Integrating Family History-Based Clinical Decision Support into Clinical Practice

    Directory of Open Access Journals (Sweden)

    Megan Doerr

    2014-03-01

    Full Text Available Family health history is a leading predictor of disease risk. Nonetheless, it is underutilized to guide care and, therefore, is ripe for health information technology intervention. To fill the family health history practice gap, Cleveland Clinic has developed a family health history collection and clinical decision support tool, MyFamily. This report describes the impact and process of implementing MyFamily into primary care, cancer survivorship and cancer genetics clinics. Ten providers participated in semi-structured interviews that were analyzed to identify opportunities for process improvement. Participants universally noted positive effects on patient care, including increases in quality, personalization of care and patient engagement. The impact on clinical workflow varied by practice setting, with differences observed in the ease of integration and the use of specific report elements. Tension between the length of the report and desired detail was appreciated. Barriers and facilitators to the process of implementation were noted, dominated by the theme of increased integration with the electronic medical record. These results fed real-time improvement cycles to reinforce clinician use. This model will be applied in future institutional efforts to integrate clinical genomic applications into practice and may be useful for other institutions considering the implementation of tools for personalizing medical management.

  20. MVO Automation Platform: Addressing Unmet Needs in Clinical Laboratories with Microcontrollers, 3D Printing, and Open-Source Hardware/Software.

    Science.gov (United States)

    Iglehart, Brian

    2018-05-01

    Laboratory automation improves test reproducibility, which is vital to patient care in clinical laboratories. Many small and specialty laboratories are excluded from the benefits of automation due to low sample number, cost, space, and/or lack of automation expertise. The Minimum Viable Option (MVO) automation platform was developed to address these hurdles and fulfill an unmet need. Consumer 3D printing enabled rapid iterative prototyping to allow for a variety of instrumentation and assay setups and procedures. Three MVO versions have been produced. MVOv1.1 successfully performed part of a clinical assay, and results were comparable to those of commercial automation. Raspberry Pi 3 Model B (RPI3) single-board computers with Sense Hardware Attached on Top (HAT) and Raspberry Pi Camera Module V2 hardware were remotely accessed and evaluated for their suitability to qualify the latest MVOv1.2 platform. Sense HAT temperature, barometric pressure, and relative humidity sensors were stable in climate-controlled environments and are useful in identifying appropriate laboratory spaces for automation placement. The RPI3 with camera plus digital dial indicator logged axis travel experiments. RPI3 with camera and Sense HAT as a light source showed promise when used for photometric dispensing tests. Individual well standard curves were necessary for well-to-well light and path length compensations.

  1. Automated Methods to Extract Patient New Information from Clinical Notes in Electronic Health Record Systems

    Science.gov (United States)

    Zhang, Rui

    2013-01-01

    The widespread adoption of Electronic Health Record (EHR) has resulted in rapid text proliferation within clinical care. Clinicians' use of copying and pasting functions in EHR systems further compounds this by creating a large amount of redundant clinical information in clinical documents. A mixture of redundant information (especially outdated…

  2. Computerized clinical decision support systems for therapeutic drug monitoring and dosing: A decision-maker-researcher partnership systematic review

    Directory of Open Access Journals (Sweden)

    Weise-Kelly Lorraine

    2011-08-01

    Full Text Available Abstract Background Some drugs have a narrow therapeutic range and require monitoring and dose adjustments to optimize their efficacy and safety. Computerized clinical decision support systems (CCDSSs may improve the net benefit of these drugs. The objective of this review was to determine if CCDSSs improve processes of care or patient outcomes for therapeutic drug monitoring and dosing. Methods We conducted a decision-maker-researcher partnership systematic review. Studies from our previous review were included, and new studies were sought until January 2010 in MEDLINE, EMBASE, Evidence-Based Medicine Reviews, and Inspec databases. Randomized controlled trials assessing the effect of a CCDSS on process of care or patient outcomes were selected by pairs of independent reviewers. A study was considered to have a positive effect (i.e., CCDSS showed improvement if at least 50% of the relevant study outcomes were statistically significantly positive. Results Thirty-three randomized controlled trials were identified, assessing the effect of a CCDSS on management of vitamin K antagonists (14, insulin (6, theophylline/aminophylline (4, aminoglycosides (3, digoxin (2, lidocaine (1, or as part of a multifaceted approach (3. Cluster randomization was rarely used (18% and CCDSSs were usually stand-alone systems (76% primarily used by physicians (85%. Overall, 18 of 30 studies (60% showed an improvement in the process of care and 4 of 19 (21% an improvement in patient outcomes. All evaluable studies assessing insulin dosing for glycaemic control showed an improvement. In meta-analysis, CCDSSs for vitamin K antagonist dosing significantly improved time in therapeutic range. Conclusions CCDSSs have potential for improving process of care for therapeutic drug monitoring and dosing, specifically insulin and vitamin K antagonist dosing. However, studies were small and generally of modest quality, and effects on patient outcomes were uncertain, with no convincing

  3. Students' stereotypes of patients as barriers to clinical decision-making.

    Science.gov (United States)

    Johnson, S M; Kurtz, M E; Tomlinson, T; Howe, K R

    1986-09-01

    The ability to formulate quick, accurate clinical judgments is stressed in medical training. Speed is usually an asset when a physician sorts through his biomedical knowledge, but it is often a liability when the physician assesses the sociocultural context of a clinical encounter. At the Michigan State University College of Osteopathic Medicine, a study was designed which graphically illustrated to beginning students that unconscious sociocultural stereotypes may influence clinical decision-making. Three entering classes of students were shown a videotape depicting five simulated patients (attractive black woman, attractive white woman, professional man, middle-aged housewife, and elderly man), each presenting with the same physical complaint. Elements of positive and negative stereotypes were incorporated into each of the portrayals, and the students rated these patients on positive and negative characteristics. The results suggested that the students attributed both positive and negative characteristics to patients on the basis of irrelevant characteristics, such as attractiveness, and with little further justification for their attributions. Such stereotypic generalizations held by students may become barriers to the students' objective clinical decision-making.

  4. Genetic Stratification in Myeloid Diseases: From Risk Assessment to Clinical Decision Support Tool

    Directory of Open Access Journals (Sweden)

    Yishai Ofran

    2014-10-01

    Full Text Available Genetic aberrations have become a dominant factor in the stratification of myeloid malignancies. Cytogenetic and a few mutation studies are the backbone of risk assessment models of myeloid malignancies which are a major consideration in clinical decisions, especially patient assignment for allogeneic stem cell transplantation. Progress in our understanding of the genetic basis of the pathogenesis of myeloid malignancies and the growing capabilities of mass sequencing may add new roles for the clinical usage of genetic data. A few recently identified mutations recognized to be associated with specific diseases or clinical scenarios may soon become part of the diagnostic criteria of such conditions. Mutational studies may also advance our capabilities for a more efficient patient selection process, assigning the most effective therapy at the best timing for each patient. The clinical utility of genetic data is anticipated to advance further with the adoption of deep sequencing and next-generation sequencing techniques. We herein suggest some future potential applications of sequential genetic data to identify pending deteriorations at time points which are the best for aggressive interventions such as allogeneic stem cell transplantation. Genetics is moving from being mostly a prognostic factor to becoming a multitasking decision support tool for hematologists. Physicians must pay attention to advances in molecular hematology as it will soon be accessible and influential for most of our patients.

  5. Clinical reasoning and population health: decision making for an emerging paradigm of health care.

    Science.gov (United States)

    Edwards, Ian; Richardson, Barbara

    2008-01-01

    Chronic conditions now provide the major disease and disability burden facing humanity. This development has necessitated a reorientation in the practice skills of health care professions away from hospital-based inpatient and outpatient care toward community-based management of patients with chronic conditions. Part of this reorientation toward community-based management of chronic conditions involves practitioners' understanding and adoption of a concept of population health management based on appropriate theoretical models of health care. Drawing on recent studies of expertise in physiotherapy, this article proposes a clinical reasoning and decision-making framework to meet these challenges. The challenge of population and community-based management of chronic conditions also provides an opportunity for physiotherapists to further clarify a professional epistemology of practice that embraces the kinds of knowledge and clinical reasoning processes used in physiotherapy practice. Three case studies related to the management of chronic musculoskeletal pain in different populations are used to exemplify the range of epistemological perspectives that underpin community-based practice. They illustrate the link between conceptualizations of practice problems and knowledge sources that are used as a basis for clinical reasoning and decision making as practitioners are increasingly required to move between the clinic and the community.

  6. Radiographer's impact on improving clinical decision-making, patient care and patient diagnosis: a pilot study

    International Nuclear Information System (INIS)

    Lam, Daniel; Egan, Ingrid; Baird, Marilyn

    2004-01-01

    This pilot study attempts to quantify the benefits of a documented radiographic clinical history through the use of the clinical history template form designed by Egan and Baird. Six radiographers completed the clinical history template for 40 patients and four radiologists included the recorded information as part of their reporting process. A focus discussion group was held between the radiographers to ascertain the level of satisfaction and benefits encountered with the use of the template form. A questionnaire was designed for the radiologists to complete regarding the usefulness of the template form with respect to the radiological reporting process. Results/Discussion: 15 cases for which the form was used demonstrated a direct benefit in respect to improved radiographic clinical decision-making. Radiographers agreed the template form aided the establishment of a stronger radiographer-patient relationship during the radiographic examination. Two radiologists agreed the form aided in establishing a radiological diagnosis and suggested the form be implemented as part of the standard departmental protocol. Despite the small sample size, there is evidence the form aided radiographic decision-making and assisted in the establishment of an accurate radiological diagnosis. The overall consensus amongst radiographers was that it enhanced radiographer-patient communication and improved the level of patient care. Copyright (2004) Australian Institute of Radiography

  7. Trail Blazing or Jam Session? Towards a New Concept of Clinical Decision-making.

    Science.gov (United States)

    Risør, Torsten

    2017-04-01

    Clinical decision-making (CDM) is key in learning to be a doctor as the defining activity in their clinical work. CDM is often portrayed in the literature as similar to 'trail blazing'; the doctor as the core agent, clearing away obstacles on the path towards diagnosis and treatment. However, in a fieldwork of young doctors in Denmark, it was difficult connect their practice to this image. This paper presents the exploration of this discrepancy in the heart of medical practice and how an alternative image emerged; that of a 'jam session'. The exploration is represented as a case-based hypothesis-testing: first, a theoretically and empirically informed hypothesis (H0) of how doctors perform CDM is developed. In H0, CDM is a stepwise process of reasoning about clinical data, often influenced by outside contextual factors. Then, H0 is tested against a case from ethnographic fieldwork with doctors going through internship. Although the case is chosen for characteristics that make it 'most likely' to verify the hypothesis, verification proves difficult. The case challenges preconceptions in CDM literature about chronology, context, objectivity, cognition, agency, and practice. The young doctor is found not to make decisions, but rather to participate in CDM; an activity akin to the dynamics found in a jam session. Their participation circles in and through four concurrent interrelated constructions that suggest a new conceptualization of CDM; a starting point for a deeper understanding of actual practice in a changing clinical environment.

  8. Making reasonable decisions: a qualitative study of medical decision making in the care of patients with a clinically significant haemoglobin disorder.

    Science.gov (United States)

    Crowther, Helen J; Kerridge, Ian

    2015-10-01

    Therapies utilized in patients with clinically significant haemoglobin disorders appear to vary between clinicians and units. This study aimed to investigate the processes of evidence implementation and medical decision making in the care of such patients in NSW, Australia. Using semi-structured interviews, 11 haematologists discussed their medical decision-making processes with particular attention paid to the use of published evidence. Transcripts were thematically analysed by a single investigator on a line-by-line basis. Decision making surrounding the care of patients with significant haemoglobin disorders varied and was deeply contextual. Three main determinants of clinical decision making were identified - factors relating to the patient and to their illness, factors specific to the clinician and the institution in which they were practising and factors related to the notion of evidence and to utility and role of evidence-based medicine in clinical practice. Clinicians pay considerable attention to medical decision making and evidence incorporation and attempt to tailor these to particular patient contexts. However, the patient context is often inferred and when discordant with the clinician's own contexture can lead to discomfort with decision recommendations. Clinicians strive to improve comfort through the use of experience and trustworthy evidence. © 2015 John Wiley & Sons, Ltd.

  9. Using decision analysis to assess comparative clinical efficacy of surgical treatment of unstable ankle fractures.

    Science.gov (United States)

    Michelson, James D

    2013-11-01

    The development of a robust treatment algorithm for ankle fractures based on well-established stability criteria has been shown to be prognostic with respect to treatment and outcomes. In parallel with the development of improved understanding of the biomechanical rationale of ankle fracture treatment has been an increased emphasis on assessing the effectiveness of medical and surgical interventions. The purpose of this study was to investigate the use of using decision analysis in the assessment of the cost effectiveness of operative treatment of ankle fractures based on the existing clinical data in the literature. Using the data obtained from a previous structured review of the ankle fracture literature, decision analysis trees were constructed using standard software. The decision nodes for the trees were based on ankle fracture stability criteria previously published. The outcomes were assessed by calculated Quality-Adjusted Life Years (QALYs) assigned to achieving normal ankle function, developing posttraumatic arthritis, or sustaining a postoperative infection. Sensitivity analysis was undertaken by varying the patient's age, incidence of arthritis, and incidence or infection. Decision analysis trees captured the essential aspects of clinical decision making in ankle fracture treatment in a clinically useful manner. In general, stable fractures yielded better outcomes with nonoperative treatment, whereas unstable fractures had better outcomes with surgery. These were consistent results over a wide range of postoperative infection rates. Varying the age of the patient did not qualitatively change the results. Between the ages of 30 and 80 years, surgery yielded higher expected QALYs than nonoperative care for unstable fractures, and generated lower QALYs than nonoperative care for stable fractures. Using local cost estimates for operative and nonoperative treatment, the incremental cost of surgery for unstable fractures was less than $40,000 per QALY (the

  10. General practitioners' decision to refer patients to dietitians: insight into the clinical reasoning process.

    Science.gov (United States)

    Pomeroy, Sylvia E M; Cant, Robyn P

    2010-01-01

    The aim of this project was to describe general practitioners' (GPs') decision-making process for reducing nutrition risk in cardiac patients through referring a patient to a dietitian. The setting was primary care practices in Victoria. The method we employed was mixed methods research: in Study 1, 30 GPs were interviewed. Recorded interviews were transcribed and narratives analysed thematically. Study 2 involved a survey of statewide random sample of GPs. Frequencies and analyses of variance were used to explore the impact of demographic variables on decisions to refer. We found that the referral decision involved four elements: (i) synthesising management information; (ii) forecasting outcomes; (iii) planning management; and (iv) actioning referrals. GPs applied cognitive and collaborative strategies to develop a treatment plan. In Study 2, doctors (248 GPs, 30%) concurred with identified barriers/enabling factors for patients' referral. There was no association between GPs' sex, age or hours worked per week and referral factors. We conclude that a GP's judgment to offer a dietetic referral to an adult patient is a four element reasoning process. Attention to how these elements interact may assist clinical decision making. Apart from the sole use of prescribed medications/surgical procedures for cardiac care, patients offered a dietetic referral were those who were considered able to commit to dietary change and who were willing to attend a dietetic consultation. Improvements in provision of patients' nutrition intervention information to GPs are needed. Further investigation is justified to determine how to resolve this practice gap.

  11. Patient Perceptions of Illness Identity in Cancer Clinical Trial Decision-Making.

    Science.gov (United States)

    Palmer-Wackerly, Angela L; Dailey, Phokeng M; Krok-Schoen, Jessica L; Rhodes, Nancy D; Krieger, Janice L

    2018-08-01

    When patients are diagnosed with cancer, they begin to negotiate their illness identity in relation to their past and future selves, their relationships, and their group memberships. Thus, how patients view their cancer in relation to their other identities may affect how and why they make particular decisions about treatment options. Using the Communication Theory of Identity (CTI), the current study explores: (1) how and why illness identity is framed across identity layers in relation to one particular cancer treatment: participation in a cancer clinical trial (CT); and (2) how and why patients experience identity conflicts while making their treatment decisions. Semi-structured, in-depth interviews were analyzed for 46 cancer patients who were offered a CT. Results of a grounded theory analysis indicated that patients expressed separate identity frames (e.g., personal, relational, and communal), aligned identity frames (e.g., personal and communal), and identity conflicts (e.g., personal-personal). This study theoretically shows how and why patient illness identity relates to cancer treatment decision-making as well as how and why patients relate (and conflict) with the cancer communal identity frame. Practical implications include how healthcare providers and family members can support patient decision-making through awareness of and accommodating to identity shifts.

  12. [Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

    Science.gov (United States)

    Wu, Dehua

    2016-01-01

    The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

  13. Automated screening for retinopathy

    Directory of Open Access Journals (Sweden)

    A. S. Rodin

    2014-07-01

    Full Text Available Retinal pathology is a common cause of an irreversible decrease of central vision commonly found amongst senior population. Detection of the earliest signs of retinal diseases can be facilitated by viewing retinal images available from the telemedicine networks. To facilitate the process of retinal images, screening software applications based on image recognition technology are currently on the various stages of development.Purpose: To develop and implement computerized image recognition software that can be used as a decision support technologyfor retinal image screening for various types of retinopathies.Methods: The software application for the retina image recognition has been developed using C++ language. It was tested on dataset of 70 images with various types of pathological features (age related macular degeneration, chorioretinitis, central serous chorioretinopathy and diabetic retinopathy.Results: It was shown that the system can achieve a sensitivity of 73 % and specificity of 72 %.Conclusion: Automated detection of macular lesions using proposed software can significantly reduce manual grading workflow. In addition, automated detection of retinal lesions can be implemented as a clinical decision support system for telemedicine screening. It is anticipated that further development of this technology can become a part of diagnostic image analysis system for the electronic health records.

  14. Clinical validation of fully automated computation of ejection fraction from gated equilibrium blood-pool scintigrams

    International Nuclear Information System (INIS)

    Reiber, J.H.C.; Lie, S.P.; Simoons, M.L.; Hoek, C.; Gerbrands, J.J.; Wijns, W.; Bakker, W.H.; Kooij, P.P.M.

    1983-01-01

    A fully automated procedure for the computation of left-ventricular ejection fraction (EF) from cardiac-gated Tc-99m blood-pool (GBP) scintigrams with fixed, dual, and variable ROI methods is described. By comparison with EF data from contrast ventriculography in 68 patients, the dual-ROI method (separate end-diastolic and end-systolic contours) was found to be the method of choice; processing time was 2 min. Success score of dual-ROI procedure was 92% as assessed from 100 GBP studies. Overall reproducibility of data acquisition and analysis was determined in 12 patients. Mean value and standard deviation of differences between repeat studies (average time interval 27 min) were 0.8% and 4.3% EF units, respectively, (r=0.98). The authors conclude that left-ventricular EF can be computed automatically from GBP scintigrams with minimal operator-interaction and good reproducibility; EFs are similar to those from contrast ventriculography

  15. "Suffering" in palliative sedation: Conceptual Analysis and Implications for Decision-Making in Clinical Practice.

    Science.gov (United States)

    Bozzaro, Claudia; Schildmann, Jan

    2018-04-21

    Palliative sedation is an increasingly used and, simultaneously, challenging practice at the end of life. Many controversies associated with this therapy are rooted in implicit differences regarding the understanding of "suffering" as prerequisite for palliative sedation. The aim of this paper is to inform the current debates by a conceptual analysis of two different philosophical accounts of suffering, (1) the subjective and holistic concept and (2) the objective and gradual concept and by a clinical-ethical analysis of the implications of each account for decisions about palliative sedation. We will show that while the subjective and holistic account of suffering fits well with the holistic approach of palliative care, there are considerable challenges to justify limits to requests for palliative sedation. By contrast, the objective and gradual account fits well with the need for an objective basis for clinical decisions in the context of palliative sedation, but runs the risk of falling short when considering the individual and subjective experience of suffering at the end of life. We will conclude with a plea for the necessity of further combined conceptual and empirical research to develop a sound and feasible understanding of suffering which can contribute to consistent decision-making about palliative sedation. Copyright © 2018. Published by Elsevier Inc.

  16. An automated tuberculosis screening strategy combining X-ray-based computer-aided detection and clinical information

    Science.gov (United States)

    Melendez, Jaime; Sánchez, Clara I.; Philipsen, Rick H. H. M.; Maduskar, Pragnya; Dawson, Rodney; Theron, Grant; Dheda, Keertan; van Ginneken, Bram

    2016-04-01

    Lack of human resources and radiological interpretation expertise impair tuberculosis (TB) screening programmes in TB-endemic countries. Computer-aided detection (CAD) constitutes a viable alternative for chest radiograph (CXR) reading. However, no automated techniques that exploit the additional clinical information typically available during screening exist. To address this issue and optimally exploit this information, a machine learning-based combination framework is introduced. We have evaluated this framework on a database containing 392 patient records from suspected TB subjects prospectively recruited in Cape Town, South Africa. Each record comprised a CAD score, automatically computed from a CXR, and 12 clinical features. Comparisons with strategies relying on either CAD scores or clinical information alone were performed. Our results indicate that the combination framework outperforms the individual strategies in terms of the area under the receiving operating characteristic curve (0.84 versus 0.78 and 0.72), specificity at 95% sensitivity (49% versus 24% and 31%) and negative predictive value (98% versus 95% and 96%). Thus, it is believed that combining CAD and clinical information to estimate the risk of active disease is a promising tool for TB screening.

  17. SeqReporter: automating next-generation sequencing result interpretation and reporting workflow in a clinical laboratory.

    Science.gov (United States)

    Roy, Somak; Durso, Mary Beth; Wald, Abigail; Nikiforov, Yuri E; Nikiforova, Marina N

    2014-01-01

    A wide repertoire of bioinformatics applications exist for next-generation sequencing data analysis; however, certain requirements of the clinical molecular laboratory limit their use: i) comprehensive report generation, ii) compatibility with existing laboratory information systems and computer operating system, iii) knowledgebase development, iv) quality management, and v) data security. SeqReporter is a web-based application developed using ASP.NET framework version 4.0. The client-side was designed using HTML5, CSS3, and Javascript. The server-side processing (VB.NET) relied on interaction with a customized SQL server 2008 R2 database. Overall, 104 cases (1062 variant calls) were analyzed by SeqReporter. Each variant call was classified into one of five report levels: i) known clinical significance, ii) uncertain clinical significance, iii) pending pathologists' review, iv) synonymous and deep intronic, and v) platform and panel-specific sequence errors. SeqReporter correctly annotated and classified 99.9% (859 of 860) of sequence variants, including 68.7% synonymous single-nucleotide variants, 28.3% nonsynonymous single-nucleotide variants, 1.7% insertions, and 1.3% deletions. One variant of potential clinical significance was re-classified after pathologist review. Laboratory information system-compatible clinical reports were generated automatically. SeqReporter also facilitated quality management activities. SeqReporter is an example of a customized and well-designed informatics solution to optimize and automate the downstream analysis of clinical next-generation sequencing data. We propose it as a model that may envisage the development of a comprehensive clinical informatics solution. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

  18. Personalised Care Plan Management Utilizing Guideline-Driven Clinical Decision Support Systems.

    Science.gov (United States)

    Laleci Erturkmen, Gokce Banu; Yuksel, Mustafa; Sarigul, Bunyamin; Lilja, Mikael; Chen, Rong; Arvanitis, Theodoros N

    2018-01-01

    Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans.

  19. Interim analysis: A rational approach of decision making in clinical trial.

    Science.gov (United States)

    Kumar, Amal; Chakraborty, Bhaswat S

    2016-01-01

    Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.

  20. Interim analysis: A rational approach of decision making in clinical trial

    Directory of Open Access Journals (Sweden)

    Amal Kumar

    2016-01-01

    Full Text Available Interim analysis of especially sizeable trials keeps the decision process free of conflict of interest while considering cost, resources, and meaningfulness of the project. Whenever necessary, such interim analysis can also call for potential termination or appropriate modification in sample size, study design, and even an early declaration of success. Given the extraordinary size and complexity today, this rational approach helps to analyze and predict the outcomes of a clinical trial that incorporate what is learned during the course of a study or a clinical development program. Such approach can also fill the gap by directing the resources toward relevant and optimized clinical trials between unmet medical needs and interventions being tested currently rather than fulfilling only business and profit goals.

  1. Sharing clinical decisions for multimorbidity case management using social network and open-source tools.

    Science.gov (United States)

    Martínez-García, Alicia; Moreno-Conde, Alberto; Jódar-Sánchez, Francisco; Leal, Sandra; Parra, Carlos

    2013-12-01

    Social networks applied through Web 2.0 tools have gained importance in health domain, because they produce improvements on the communication and coordination capabilities among health professionals. This is highly relevant for multimorbidity patients care because there is a large number of health professionals in charge of patient care, and this requires to obtain clinical consensus in their decisions. Our objective is to develop a tool for collaborative work among health professionals for multimorbidity patient care. We describe the architecture to incorporate decision support functionalities in a social network tool to enable the adoption of shared decisions among health professionals from different care levels. As part of the first stage of the project, this paper describes the results obtained in a pilot study about acceptance and use of the social network component in our healthcare setting. At Virgen del Rocío University Hospital we have designed and developed the Shared Care Platform (SCP) to provide support in the continuity of care for multimorbidity patients. The SCP has two consecutively developed components: social network component, called Clinical Wall, and Clinical Decision Support (CDS) system. The Clinical Wall contains a record where health professionals are able to debate and define shared decisions. We conducted a pilot study to assess the use and acceptance of the SCP by healthcare professionals through questionnaire based on the theory of the Technology Acceptance Model. In March 2012 we released and deployed the SCP, but only with the social network component. The pilot project lasted 6 months in the hospital and 2 primary care centers. From March to September 2012 we created 16 records in the Clinical Wall, all with a high priority. A total of 10 professionals took part in the exchange of messages: 3 internists and 7 general practitioners generated 33 messages. 12 of the 16 record (75%) were answered by the destination health professionals

  2. Decision theory and the evaluation of risks and benefits of clinical trials.

    Science.gov (United States)

    Bernabe, Rosemarie D C; van Thiel, Ghislaine J M W; Raaijmakers, Jan A M; van Delden, Johannes J M

    2012-12-01

    Research ethics committees (RECs) are tasked to assess the risks and the benefits of a clinical trial. In previous studies, it was shown that RECs find this task difficult, if not impossible, to do. The current approaches to benefit-risk assessment (i.e. Component Analysis and the Net Risk Test) confound the various risk-benefit tasks, and as such, make balancing impossible. In this article, we show that decision theory, specifically through the expected utility theory and multiattribute utility theory, enable for an explicit and ethically weighted risk-benefit evaluation. This makes a balanced ethical justification possible, and thus a more rationally defensible decision making. Copyright © 2012 Elsevier Ltd. All rights reserved.

  3. Clinical decision support improves quality of telephone triage documentation--an analysis of triage documentation before and after computerized clinical decision support.

    Science.gov (United States)

    North, Frederick; Richards, Debra D; Bremseth, Kimberly A; Lee, Mary R; Cox, Debra L; Varkey, Prathibha; Stroebel, Robert J

    2014-03-20

    Clinical decision support (CDS) has been shown to be effective in improving medical safety and quality but there is little information on how telephone triage benefits from CDS. The aim of our study was to compare triage documentation quality associated with the use of a clinical decision support tool, ExpertRN©. We examined 50 triage documents before and after a CDS tool was used in nursing triage. To control for the effects of CDS training we had an additional control group of triage documents created by nurses who were trained in the CDS tool, but who did not use it in selected notes. The CDS intervention cohort of triage notes was compared to both the pre-CDS notes and the CDS trained (but not using CDS) cohort. Cohorts were compared using the documentation standards of the American Academy of Ambulatory Care Nursing (AAACN). We also compared triage note content (documentation of associated positive and negative features relating to the symptoms, self-care instructions, and warning signs to watch for), and documentation defects pertinent to triage safety. Three of five AAACN documentation standards were significantly improved with CDS. There was a mean of 36.7 symptom features documented in triage notes for the CDS group but only 10.7 symptom features in the pre-CDS cohort (p < 0.0001) and 10.2 for the cohort that was CDS-trained but not using CDS (p < 0.0001). The difference between the mean of 10.2 symptom features documented in the pre-CDS and the mean of 10.7 symptom features documented in the CDS-trained but not using was not statistically significant (p = 0.68). CDS significantly improves triage note documentation quality. CDS-aided triage notes had significantly more information about symptoms, warning signs and self-care. The changes in triage documentation appeared to be the result of the CDS alone and not due to any CDS training that came with the CDS intervention. Although this study shows that CDS can improve documentation, further study is needed

  4. New clinical validation method for automated sphygmomanometer: a proposal by Japan ISO-WG for sphygmomanometer standard.

    Science.gov (United States)

    Shirasaki, Osamu; Asou, Yosuke; Takahashi, Yukio

    2007-12-01

    Owing to fast or stepwise cuff deflation, or measuring at places other than the upper arm, the clinical accuracy of most recent automated sphygmomanometers (auto-BPMs) cannot be validated by one-arm simultaneous comparison, which would be the only accurate validation method based on auscultation. Two main alternative methods are provided by current standards, that is, two-arm simultaneous comparison (method 1) and one-arm sequential comparison (method 2); however, the accuracy of these validation methods might not be sufficient to compensate for the suspicious accuracy in lateral blood pressure (BP) differences (LD) and/or BP variations (BPV) between the device and reference readings. Thus, the Japan ISO-WG for sphygmomanometer standards has been studying a new method that might improve validation accuracy (method 3). The purpose of this study is to determine the appropriateness of method 3 by comparing immunity to LD and BPV with those of the current validation methods (methods 1 and 2). The validation accuracy of the above three methods was assessed in human participants [N=120, 45+/-15.3 years (mean+/-SD)]. An oscillometric automated monitor, Omron HEM-762, was used as the tested device. When compared with the others, methods 1 and 3 showed a smaller intra-individual standard deviation of device error (SD1), suggesting their higher reproducibility of validation. The SD1 by method 2 (P=0.004) significantly correlated with the participant's BP, supporting our hypothesis that the increased SD of device error by method 2 is at least partially caused by essential BPV. Method 3 showed a significantly (P=0.0044) smaller interparticipant SD of device error (SD2), suggesting its higher interparticipant consistency of validation. Among the methods of validation of the clinical accuracy of auto-BPMs, method 3, which showed the highest reproducibility and highest interparticipant consistency, can be proposed as being the most appropriate.

  5. The Research of Clinical Decision Support System Based on Three-Layer Knowledge Base Model

    Directory of Open Access Journals (Sweden)

    Yicheng Jiang

    2017-01-01

    Full Text Available In many clinical decision support systems, a two-layer knowledge base model (disease-symptom of rule reasoning is used. This model often does not express knowledge very well since it simply infers disease from the presence of certain symptoms. In this study, we propose a three-layer knowledge base model (disease-symptom-property to utilize more useful information in inference. The system iteratively calculates the probability of patients who may suffer from diseases based on a multisymptom naive Bayes algorithm, in which the specificity of these disease symptoms is weighted by the estimation of the degree of contribution to diagnose the disease. It significantly reduces the dependencies between attributes to apply the naive Bayes algorithm more properly. Then, the online learning process for parameter optimization of the inference engine was completed. At last, our decision support system utilizing the three-layer model was formally evaluated by two experienced doctors. By comparisons between prediction results and clinical results, our system can provide effective clinical recommendations to doctors. Moreover, we found that the three-layer model can improve the accuracy of predictions compared with the two-layer model. In light of some of the limitations of this study, we also identify and discuss several areas that need continued improvement.

  6. A study of diverse clinical decision support rule authoring environments and requirements for integration

    Directory of Open Access Journals (Sweden)

    Zhou Li

    2012-11-01

    Full Text Available Abstract Background Efficient rule authoring tools are critical to allow clinical Knowledge Engineers (KEs, Software Engineers (SEs, and Subject Matter Experts (SMEs to convert medical knowledge into machine executable clinical decision support rules. The goal of this analysis was to identify the critical success factors and challenges of a fully functioning Rule Authoring Environment (RAE in order to define requirements for a scalable, comprehensive tool to manage enterprise level rules. Methods The authors evaluated RAEs in active use across Partners Healthcare, including enterprise wide, ambulatory only, and system specific tools, with a focus on rule editors for reminder and medication rules. We conducted meetings with users of these RAEs to discuss their general experience and perceived advantages and limitations of these tools. Results While the overall rule authoring process is similar across the 10 separate RAEs, the system capabilities and architecture vary widely. Most current RAEs limit the ability of the clinical decision support (CDS interventions to be standardized, sharable, interoperable, and extensible. No existing system meets all requirements defined by knowledge management users. Conclusions A successful, scalable, integrated rule authoring environment will need to support a number of key requirements and functions in the areas of knowledge representation, metadata, terminology, authoring collaboration, user interface, integration with electronic health record (EHR systems, testing, and reporting.

  7. Development and impact of computerised decision support systems for clinical management of depression: A systematic review.

    Science.gov (United States)

    Triñanes, Yolanda; Atienza, Gerardo; Louro-González, Arturo; de-las-Heras-Liñero, Elena; Alvarez-Ariza, María; Palao, Diego J

    2015-01-01

    One of the proposals for improving clinical practice is to introduce computerised decision support systems (CDSS) and integrate these with electronic medical records. Accordingly, this study sought to systematically review evidence on the effectiveness of CDSS in the management of depression. A search was performed in Medline, EMBASE and PsycInfo, in order to do this. The quality of quantitative studies was assessed using the SIGN method, and qualitative studies using the CASPe checklist. Seven studies were identified (3 randomised clinical trials, 3 non-randomised trials, and one qualitative study). The CDSS assessed incorporated content drawn from guidelines and other evidence-based products. In general, the CDSS had a positive impact on different aspects, such as the screening and diagnosis, treatment, improvement in depressive symptoms and quality of life, and referral of patients. The use of CDSS could thus serve to optimise care of depression in various scenarios by providing recommendations based on the best evidence available and facilitating decision-making in clinical practice. Copyright © 2014 SEP y SEPB. Published by Elsevier España. All rights reserved.

  8. Translating shared decision-making into health care clinical practices: Proof of concepts

    Directory of Open Access Journals (Sweden)

    St-Jacques Sylvie

    2008-01-01

    Full Text Available Abstract Background There is considerable interest today in shared decision-making (SDM, defined as a decision-making process jointly shared by patients and their health care provider. However, the data show that SDM has not been broadly adopted yet. Consequently, the main goal of this proposal is to bring together the resources and the expertise needed to develop an interdisciplinary and international research team on the implementation of SDM in clinical practice using a theory-based dyadic perspective. Methods Participants include researchers from Canada, US, UK, and Netherlands, representing medicine, nursing, psychology, community health and epidemiology. In order to develop a collaborative research network that takes advantage of the expertise of the team members, the following research activities are planned: 1 establish networking and on-going communication through internet-based forum, conference calls, and a bi-weekly e-bulletin; 2 hold a two-day workshop with two key experts (one in theoretical underpinnings of behavioral change, and a second in dyadic data analysis, and invite all investigators to present their views on the challenges related to the implementation of SDM in clinical practices; 3 conduct a secondary analyses of existing dyadic datasets to ensure that discussion among team members is grounded in empirical data; 4 build capacity with involvement of graduate students in the workshop and online forum; and 5 elaborate a position paper and an international multi-site study protocol. Discussion This study protocol aims to inform researchers, educators, and clinicians interested in improving their understanding of effective strategies to implement shared decision-making in clinical practice using a theory-based dyadic perspective.

  9. Emergency nurses' knowledge, attitude and clinical decision making skills about pain.

    Science.gov (United States)

    Ucuzal, Meral; Doğan, Runida

    2015-04-01

    Pain is the most common reason that patients come to the emergency department. Emergency nurses have an indispensable role in the management of this pain. The aim of this study was to examine emergency nurses' knowledge, attitude and clinical decision-making skills about pain. This descriptive study was conducted in a state and a university hospital between September and October 2012 in Malatya, Turkey. Of 98 nurses working in the emergency departments of these two hospitals, 57 returned the questionnaires. The response rate was 58%. Data were collected using the Demographic Information Questionnaire, Knowledge and Attitude Questionnaire about Pain and Clinical Decision Making Survey. Frequency, percentage, mean and standard deviation were used to evaluate data. 75.4% of participant nurses knew that patients' own statement about their pain was the most reliable indicator during pain assessment. Almost half of the nurses believed that patients should be encouraged to endure the pain as much as possible before resorting to a pain relief method. The results also indicate that most of nurses think that a sleeping patient does not have any pain and pain relief should be postponed as it can influence the diagnosis negatively. It is determined that the pain scale was not used frequently. Only 35.1% of nurses reported keeping records of pain. Despite all the recommendations of substantial past research the results of this study indicate that emergency nurses continue to demonstrate inadequate knowledge, clinical decision-making skills and negative attitudes about pain. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. A diagnosis-based clinical decision rule for spinal pain part 2: review of the literature

    Directory of Open Access Journals (Sweden)

    Hurwitz Eric L

    2008-08-01

    Full Text Available Abstract Background Spinal pain is a common and often disabling problem. The research on various treatments for spinal pain has, for the most part, suggested that while several interventions have demonstrated mild to moderate short-term benefit, no single treatment has a major impact on either pain or disability. There is great need for more accurate diagnosis in patients with spinal pain. In a previous paper, the theoretical model of a diagnosis-based clinical decision rule was presented. The approach is designed to provide the clinician with a strategy for arriving at a specific working diagnosis from which treatment decisions can be made. It is based on three questions of diagnosis. In the current paper, the literature on the reliability and validity of the assessment procedures that are included in the diagnosis-based clinical decision rule is presented. Methods The databases of Medline, Cinahl, Embase and MANTIS were searched for studies that evaluated the reliability and validity of clinic-based diagnostic procedures for patients with spinal pain that have relevance for questions 2 (which investigates characteristics of the pain source and 3 (which investigates perpetuating factors of the pain experience. In addition, the reference list of identified papers and authors' libraries were searched. Results A total of 1769 articles were retrieved, of which 138 were deemed relevant. Fifty-one studies related to reliability and 76 related to validity. One study evaluated both reliability and validity. Conclusion Regarding some aspects of the DBCDR, there are a number of studies that allow the clinician to have a reasonable degree of confidence in his or her findings. This is particularly true for centralization signs, neurodynamic signs and psychological perpetuating factors. There are other aspects of the DBCDR in which a lesser degree of confidence is warranted, and in which further research is needed.

  11. Automatic Decision Support for Clinical Diagnostic Literature Using Link Analysis in a Weighted Keyword Network.

    Science.gov (United States)

    Li, Shuqing; Sun, Ying; Soergel, Dagobert

    2017-12-23

    We present a novel approach to recommending articles from the medical literature that support clinical diagnostic decision-making, giving detailed descriptions of the associated ideas and principles. The specific goal is to retrieve biomedical articles that help answer questions of a specified type about a particular case. Based on the filtered keywords, MeSH(Medical Subject Headings) lexicon and the automatically extracted acronyms, the relationship between keywords and articles was built. The paper gives a detailed description of the process of by which keywords were measured and relevant articles identified based on link analysis in a weighted keywords network. Some important challenges identified in this study include the extraction of diagnosis-related keywords and a collection of valid sentences based on the keyword co-occurrence analysis and existing descriptions of symptoms. All data were taken from medical articles provided in the TREC (Text Retrieval Conference) clinical decision support track 2015. Ten standard topics and one demonstration topic were tested. In each case, a maximum of five articles with the highest relevance were returned. The total user satisfaction of 3.98 was 33% higher than average. The results also suggested that the smaller the number of results, the higher the average satisfaction. However, a few shortcomings were also revealed since medical literature recommendation for clinical diagnostic decision support is so complex a topic that it cannot be fully addressed through the semantic information carried solely by keywords in existing descriptions of symptoms. Nevertheless, the fact that these articles are actually relevant will no doubt inspire future research.

  12. Exploring a Laboratory Model of Pharmacogenetics as Applied to Clinical Decision Making

    Directory of Open Access Journals (Sweden)

    David F. Kisor

    2013-01-01

    Full Text Available Objective: To evaluate a pilot of a laboratory model for relating pharmacogenetics to clinical decision making. Case Study: This pilot was undertaken and evaluated to help determine if a pharmacogenetics laboratory should be included in the core Doctor of Pharmacy curriculum. The placement of the laboratory exercise in the curriculum was determined by identifying the point in the curriculum where the students had been introduced to the chemistry of deoxyribonucleic acid (DNA as well as instructed on the chemistry of genetic variation. The laboratory included cytochrome P450 2C19 genotyping relative to the *2 variant. Twenty-four students served as the pilot group. Students provided buccal swabs as the source of DNA. Students stabilized the samples and were then provided instructions related to sample preparation, polymerase chain reaction, and gel electrophoresis. The results were reported as images of gels. Students used a reference gel image to compare their results to. Students then applied a dosing algorithm to make a "clinical decision" relative to clopidogrel use. Students were offered a post laboratory survey regarding attitudes toward the laboratory. Twenty-four students completed the laboratory with genotyping results being provided for 22 students (91.7%. Sixteen students were wild-type (*1/*1, while six students were heterozygous (*1/*2. Twenty-three students (96% completed the post laboratory survey. All 23 agreed (6, 26.1% or strongly agreed (17, 73.9% that the laboratory "had relevance and value in the pharmacy curriculum" Conclusion: The post pilot study survey exploring a laboratory model for pharmacogenetics related to clinical decision making indicated that such a laboratory would be viewed positively by students. This model may be adopted by colleges to expand pharmacogenetics education.   Type: Case Study

  13. Automatic identification of high impact articles in PubMed to support clinical decision making.

    Science.gov (United States)

    Bian, Jiantao; Morid, Mohammad Amin; Jonnalagadda, Siddhartha; Luo, Gang; Del Fiol, Guilherme

    2017-09-01

    The practice of evidence-based medicine involves integrating the latest best available evidence into patient care decisions. Yet, critical barriers exist for clinicians' retrieval of evidence that is relevant for a particular patient from primary sources such as randomized controlled trials and meta-analyses. To help address those barriers, we investigated machine learning algorithms that find clinical studies with high clinical impact from PubMed®. Our machine learning algorithms use a variety of features including bibliometric features (e.g., citation count), social media attention, journal impact factors, and citation metadata. The algorithms were developed and evaluated with a gold standard composed of 502 high impact clinical studies that are referenced in 11 clinical evidence-based guidelines on the treatment of various diseases. We tested the following hypotheses: (1) our high impact classifier outperforms a state-of-the-art classifier based on citation metadata and citation terms, and PubMed's® relevance sort algorithm; and (2) the performance of our high impact classifier does not decrease significantly after removing proprietary features such as citation count. The mean top 20 precision of our high impact classifier was 34% versus 11% for the state-of-the-art classifier and 4% for PubMed's® relevance sort (p=0.009); and the performance of our high impact classifier did not decrease significantly after removing proprietary features (mean top 20 precision=34% vs. 36%; p=0.085). The high impact classifier, using features such as bibliometrics, social media attention and MEDLINE® metadata, outperformed previous approaches and is a promising alternative to identifying high impact studies for clinical decision support. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

    Science.gov (United States)

    Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

    2017-06-01

    This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

  15. Integrating complex business processes for knowledge-driven clinical decision support systems.

    Science.gov (United States)

    Kamaleswaran, Rishikesan; McGregor, Carolyn

    2012-01-01

    This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

  16. Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders

    DEFF Research Database (Denmark)

    Gross, Douglas P; Armijo-Olivo, Susan; Shaw, William S

    2016-01-01

    Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying...... the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses...

  17. Real-Time Analysis of a Sensor's Data for Automated Decision Making in an IoT-Based Smart Home.

    Science.gov (United States)

    Khan, Nida Saddaf; Ghani, Sayeed; Haider, Sajjad

    2018-05-25

    IoT devices frequently generate large volumes of streaming data and in order to take advantage of this data, their temporal patterns must be learned and identified. Streaming data analysis has become popular after being successfully used in many applications including forecasting electricity load, stock market prices, weather conditions, etc. Artificial Neural Networks (ANNs) have been successfully utilized in understanding the embedded interesting patterns/behaviors in the data and forecasting the future values based on it. One such pattern is modelled and learned in the present study to identify the occurrence of a specific pattern in a Water Management System (WMS). This prediction aids in making an automatic decision support system, to switch OFF a hydraulic suction pump at the appropriate time. Three types of ANN, namely Multi-Input Multi-Output (MIMO), Multi-Input Single-Output (MISO), and Recurrent Neural Network (RNN) have been compared, for multi-step-ahead forecasting, on a sensor's streaming data. Experiments have shown that RNN has the best performance among three models and based on its prediction, a system can be implemented to make the best decision with 86% accuracy.

  18. [Descemet's stripping automated endothelial keratoplasty (DEAEK). Systematic review of clinical-effectiveness and safety].

    Science.gov (United States)

    Paz-Valiñas, L; de la Fuente-Cid, R; de Rojas-Silva, M V; López-Rodríguez, I; López-García, M

    2015-04-01

    To conduct a systematic review of the efficacy/effectiveness, safety and cost of Descemet's stripping automated endothelial keratoplasty (DSAEK) technique in patients with corneal endothelial failure. Comprehensive literature search conducted in the main biomedical databases from January-May 2012. Following a critical perusal of the total of 485 abstracts retrieved, 16 case series and one economic evaluation study were included. Corrected distance visual acuity and uncorrected distance visual acuity improved after treatment with DSAEK, attaining values of 0.6 to 0.8 and 0.5 respectively. The degree of post-DSAEK astigmatism was not significant with respect to baseline values. The main complications were graft dislocation-detachment (1.5-23%), primary failure (0-12%) and endothelial rejection (0.8-8.5%). In Fuchs' dystrophy and bullous keratopathy, data on the effectiveness of DSAEK indicate post-intervention improvement in uncorrected and corrected distance visual acuity. Astigmatism arising after DSAEK was not significant. The most significant post-DSAEK complications are linked to the viability of the graft, with the most frequent complications being dislocation-detachment and, to a lesser extent, endothelial rejection. The studies that assess DSAEK are case series, and for the most part retrospective. The quality of this type of studies is both low and limited. Copyright © 2012 Sociedad Española de Oftalmología. Published by Elsevier España, S.L.U. All rights reserved.

  19. Clinical application of automated Greulich-Pyle bone age determination in children with short stature

    International Nuclear Information System (INIS)

    Martin, David D.; Deusch, Dorothee; Schweizer, Roland; Binder, Gerhard; Ranke, Michael B.; Thodberg, Hans Henrik

    2009-01-01

    Bone age (BA) rating is time consuming and highly rater dependent. To adjust the fully automated BoneXpert method to agree with the manual Greulich and Pyle BA (GP BA) ratings of five raters and to validate the accuracy for short children. A total of 1,097 left hand radiographs from 188 children with short stature, including growth hormone deficiency (44%) and Turner syndrome (29%) were evaluated. BoneXpert rejected 14 of the 1,097 radiographs, and deviated by more than 1.9 years from the operator BA for 27 radiographs. These were rerated blindly by four operators. Of the 27 new ratings, 26 were within 1.9 years of the automatic BA values. The root mean square deviation between manual and automatic rating was 0.72 years (95% CI 0.69-0.75). BoneXpert's ability to process 99% of images automatically without errors, and to obtain good agreement with an operator suggests that the method is efficient and reliable for short children. (orig.)

  20. Current concepts in clinical research: web-based, automated, arthroscopic surgery prospective database registry.

    Science.gov (United States)

    Lubowitz, James H; Smith, Patrick A

    2012-03-01

    In 2011, postsurgical patient outcome data may be compiled in a research registry, allowing comparative-effectiveness research and cost-effectiveness analysis by use of Health Insurance Portability and Accountability Act